{"as_of":"2026-08-21T19:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:65dd23a3e0204f772f7ea0a794103794c2d15394e7ab09a543ae7913d22f4c79","coverage":[{"denominator":111,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:01:57.448378Z","state":"measured"},{"denominator":110,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":110,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T15:07:59.132190Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-06-29T12:53:26.512979Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.16582","snapshot_observed_at":"2026-08-05T21:12:11.380262Z","title":"O2-searcher: A searching-based agent model for open-domain open-ended question answering","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.09303","last_updated":"2025-08-12T19:38:21Z","snapshot_observed_at":"2026-08-19T19:48:28.938884Z","submitted_at":"2025-08-12T19:38:21Z","title":"ParallelSearch: Train your LLMs to Decompose Query and Search Sub-queries in Parallel with Reinforcement Learning","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-05T21:12:11.380262Z"},"links":{"cited_paper":"/paper/2505.16582","citing_paper":"/paper/2508.09303"},"observation_digest":"sha256:838a4e0daab1a876b77a0424ac2ccc1370805947cf0fb46550988b6f62333686","observation_id":"db71740e-3dcd-4e2e-9a94-e4126188259d","resolution":{"observed_at":"2026-08-05T21:12:11.380262Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"cited_work":{"arxiv_id":"2505.16582","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.16582","snapshot_observed_at":"2026-06-29T12:53:26.512979Z","title":"O2-searcher: A searching-based agent model for open-domain open-ended question answering","venue":null,"work_id":"eafd4f43-5373-4ff5-a2d3-6dda4860daf6","year":2025},"citing_paper":{"arxiv_id":"2510.00861","last_updated":"2026-04-20T08:17:44Z","snapshot_observed_at":"2026-08-11T07:29:40.321860Z","submitted_at":"2025-10-01T13:10:36Z","title":"Erase to Improve: Erasable Reinforcement Learning for Search-Augmented LLMs","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-18T11:06:20.058342Z"},"links":{"cited_paper":"/paper/2505.16582","citing_paper":"/paper/2510.00861"},"observation_digest":"sha256:f1420458b04adaa4b8dad43cae2c8cbda926a5d505616d501c35b15e1dab9552","observation_id":"95a35b92-324c-41c0-afe5-153aa7987f46","resolution":{"observed_at":"2026-05-18T11:11:18.194028Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"cited_work":{"arxiv_id":"2505.16582","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.16582","snapshot_observed_at":"2026-06-29T12:53:26.512979Z","title":"O2-searcher: A searching-based agent model for open-domain open-ended question answering","venue":null,"work_id":"eafd4f43-5373-4ff5-a2d3-6dda4860daf6","year":2025},"citing_paper":{"arxiv_id":"2510.16079","last_updated":"2026-05-16T02:57:47Z","snapshot_observed_at":"2026-08-20T17:07:30.962332Z","submitted_at":"2025-10-17T12:03:16Z","title":"EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-18T06:19:44.360734Z"},"links":{"cited_paper":"/paper/2505.16582","citing_paper":"/paper/2510.16079"},"observation_digest":"sha256:37bedd8742ca8110ca619e318e7c7ff7506b6e098cef465da4705d796b8d1d2f","observation_id":"4a4d953d-6c70-46e2-bf01-d7543508163a","resolution":{"observed_at":"2026-05-18T06:20:58.379213Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"cited_work":{"arxiv_id":"2505.16582","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.16582","snapshot_observed_at":"2026-06-29T12:53:26.512979Z","title":"O2-searcher: A searching-based agent model for open-domain open-ended question answering","venue":null,"work_id":"eafd4f43-5373-4ff5-a2d3-6dda4860daf6","year":2025},"citing_paper":{"arxiv_id":"2510.16079","last_updated":"2026-05-16T02:57:47Z","snapshot_observed_at":"2026-08-20T17:07:30.962332Z","submitted_at":"2025-10-17T12:03:16Z","title":"EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-21T20:50:06.642976Z"},"links":{"cited_paper":"/paper/2505.16582","citing_paper":"/paper/2510.16079"},"observation_digest":"sha256:6d61c536a6da1f180d1473677f7dc4285aa42c7ceb753af4daf3aa8a174fbc1e","observation_id":"c6fa54ac-2972-4ee1-9caa-0ab9c54c5381","resolution":{"observed_at":"2026-05-21T20:50:36.521411Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.16582","snapshot_observed_at":"2026-08-03T10:55:09.411210Z","title":"Jianbiao Mei, Tao Hu, Daocheng Fu, Licheng Wen, Xue- meng Yang, Rong Wu, Pinlong Cai, Xinyu Cai, Xing Gao, Yu Yang, and 1 others","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.08173","last_updated":"2026-06-02T11:13:10Z","snapshot_observed_at":"2026-08-13T09:02:36.940762Z","submitted_at":"2026-01-13T03:09:18Z","title":"The Agent's First Day: Benchmarking Learning, Exploration, and Scheduling in the Workplace Scenarios","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-03T10:55:09.411210Z"},"links":{"cited_paper":"/paper/2505.16582","citing_paper":"/paper/2601.08173"},"observation_digest":"sha256:9055b1799955fd7a8e50af8b650a95d776a9bc089e8b9907d5dc1cfb85877e4b","observation_id":"38e62f24-3abf-4f9f-87f5-f16567de907c","resolution":{"observed_at":"2026-08-03T10:55:09.411210Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"cited_work":{"arxiv_id":"2505.16582","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.16582","snapshot_observed_at":"2026-06-29T12:53:26.512979Z","title":"O2-searcher: A searching-based agent model for open-domain open-ended question answering","venue":null,"work_id":"eafd4f43-5373-4ff5-a2d3-6dda4860daf6","year":2025},"citing_paper":{"arxiv_id":"2605.30824","last_updated":"2026-05-29T04:18:55Z","snapshot_observed_at":"2026-08-20T05:21:01.739912Z","submitted_at":"2026-05-29T04:18:55Z","title":"Planner-Centric Reinforcement Learning for Deep Research with Structure-Aware Reward","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-06-28T22:30:00.735630Z"},"links":{"cited_paper":"/paper/2505.16582","citing_paper":"/paper/2605.30824"},"observation_digest":"sha256:0acfadb616645395dd70e3278d7550c3609dfc2e2940d2a0a8df9d8b240c3579","observation_id":"7b446caa-dc00-470e-b490-ce6343ff6535","resolution":{"observed_at":"2026-06-28T22:32:44.034005Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"cited_work":{"arxiv_id":"2505.16582","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.16582","snapshot_observed_at":"2026-06-29T12:53:26.512979Z","title":"O2-searcher: A searching-based agent model for open-domain open-ended question answering","venue":null,"work_id":"eafd4f43-5373-4ff5-a2d3-6dda4860daf6","year":2025},"citing_paper":{"arxiv_id":"2606.26122","last_updated":"2026-05-27T21:21:42Z","snapshot_observed_at":"2026-08-15T22:31:05.444033Z","submitted_at":"2026-05-27T21:21:42Z","title":"DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-29T12:50:16.625077Z"},"links":{"cited_paper":"/paper/2505.16582","citing_paper":"/paper/2606.26122"},"observation_digest":"sha256:92aeb3ec2756d4d1d681a135eae1c73b2f3f420d925daa45c0d8575590e4a3f9","observation_id":"baf03880-f8ab-4fe3-9637-5e937418abcc","resolution":{"observed_at":"2026-06-29T12:53:26.514372Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.16582","snapshot_observed_at":"2026-07-31T12:39:14.014060Z","title":"o2-searcher: A searching-based agent model for open-domain open-ended question answering.arXiv preprint arXiv:2505.16582, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.28272","last_updated":"2026-07-30T14:25:49Z","snapshot_observed_at":"2026-08-18T12:33:40.733069Z","submitted_at":"2026-07-30T14:25:49Z","title":"MemHarness: Memory Is Reconstructed, Not Replayed","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-31T12:39:14.014060Z"},"links":{"cited_paper":"/paper/2505.16582","citing_paper":"/paper/2607.28272"},"observation_digest":"sha256:f9ecc16366850efbbd4b24e57f00dee75b72e16dfb2434e0a3c4f37e6085058b","observation_id":"09a51526-e474-4168-9506-abd0a408f3fd","resolution":{"observed_at":"2026-07-31T12:39:14.014060Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.16582","snapshot_observed_at":"2026-08-15T15:07:59.132190Z","title":"arXiv preprint arXiv:2505.16582 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.01822","last_updated":"2026-08-03T07:29:11Z","snapshot_observed_at":"2026-08-17T21:44:04.212148Z","submitted_at":"2026-08-03T07:29:11Z","title":"SearchMaster: Grounded and Regulated Self-Play for Search Agents","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-15T15:07:59.132190Z"},"links":{"cited_paper":"/paper/2505.16582","citing_paper":"/paper/2608.01822"},"observation_digest":"sha256:612704ea11942ec0a6fd3e55279df4f3f1dc783133b366b34a6c941c04b44f51","observation_id":"9e35b822-9552-4fc3-9095-7a7f92e91990","resolution":{"observed_at":"2026-08-15T15:07:59.132190Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.16582","snapshot_observed_at":"2026-08-04T15:12:55.912187Z","title":"2025 , archivePrefix =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.02097","last_updated":"2026-08-03T11:58:21Z","snapshot_observed_at":"2026-08-15T22:59:26.336051Z","submitted_at":"2026-08-03T11:58:21Z","title":"Fetch-then-Explore: Decoupling Selection from Extraction over a Persistent Workspace for Search Agents","version":1},"reference_index":151,"source":"arxiv_source","source_observed_at":"2026-08-04T15:12:55.912187Z"},"links":{"cited_paper":"/paper/2505.16582","citing_paper":"/paper/2608.02097"},"observation_digest":"sha256:01b9d1f93adf44af4e454178df6f6956c709dac5bc942d80d421e60c822bf2d3","observation_id":"141553b0-a2d5-49f9-9141-ef0e292b767e","resolution":{"observed_at":"2026-08-04T15:12:55.912187Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2505.16582/citation-record","integrity":"/paper/2505.16582/integrity","json":"/paper/2505.16582/citation-record.json","paper":"/paper/2505.16582"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.20201","last_updated":"2025-03-26T03:51:32Z","snapshot_observed_at":"2026-08-20T12:09:39.887157Z","submitted_at":"2025-03-26T03:51:32Z","title":"Open Deep Search: Democratizing Search with Open-source Reasoning Agents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.20201","snapshot_observed_at":"2026-08-07T15:01:47.195572Z","title":"Open deep search: Democratizing search with open-source reasoning agents.arXiv preprint arXiv:2503.20201, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:47.195572Z"},"links":{"cited_paper":"/paper/2503.20201","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:7433f719155e8eeebe765228bd240d491ddd2ec9091cb32ba7ec7e2c394f84f4","observation_id":"847a1c54-3737-4fa3-a66e-b5de5a9feefe","resolution":{"observed_at":"2026-08-07T15:01:47.195572Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:47.242590Z","title":"Self-rag: Learning to retrieve, generate, and critique through self-reflection","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:47.242590Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:335eb7c17b88c601697f0ce539d28491003bdab0573ee35a24eec74eecd836d7","observation_id":"8ba48282-e552-4bfb-a28e-365a4b41ba1b","resolution":{"observed_at":"2026-08-07T15:01:47.242590Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:47.307736Z","title":"Scaling instruction-finetuned language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:47.307736Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:f002f060e84329afb8a640c24ea0bb07dbc2e58143af0833a66b61fec8fc6cbc","observation_id":"fcb008d6-51fa-4e1f-a13f-b035257be31b","resolution":{"observed_at":"2026-08-07T15:01:47.307736Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-14T02:43:01.480086Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-08-07T15:01:47.367232Z","title":"Training verifiers to solve math word problems.arXiv preprint arXiv:2110.14168, 2021","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:47.367232Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:6d9ea6c8d65bb569ea038e1a719838742fb75342a4e9548e48a942c7f32473f3","observation_id":"ff85960c-cd99-4f2f-b1a4-b209315cfd3f","resolution":{"observed_at":"2026-08-07T15:01:47.367232Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.01456","last_updated":"2025-09-26T09:25:31Z","snapshot_observed_at":"2026-08-20T04:08:34.710482Z","submitted_at":"2025-02-03T15:43:48Z","title":"Process Reinforcement through Implicit Rewards","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.01456","snapshot_observed_at":"2026-08-07T15:01:47.477105Z","title":"Process reinforcement through implicit rewards.arXiv preprint arXiv:2502.01456, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:47.477105Z"},"links":{"cited_paper":"/paper/2502.01456","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:288db7864fa7681318c929afcd3f160570fa153395fe93674198ffc448136b63","observation_id":"b6f8af41-810c-4400-93f2-b0721fb8dd03","resolution":{"observed_at":"2026-08-07T15:01:47.477105Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.09572","last_updated":"2025-04-22T17:56:22Z","snapshot_observed_at":"2026-08-14T20:53:01.569151Z","submitted_at":"2025-03-12T17:40:52Z","title":"Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.09572","snapshot_observed_at":"2026-08-07T15:01:47.550560Z","title":"Plan-and-act: Improving planning of agents for long-horizon tasks","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:47.550560Z"},"links":{"cited_paper":"/paper/2503.09572","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:00fc0f3f2b783d5139d03909fc97e3b31d6a11aef669b6792e82099905a0c874","observation_id":"81c929cc-f245-4362-a33c-4ae4bb8766fd","resolution":{"observed_at":"2026-08-07T15:01:47.550560Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:47.648803Z","title":"Trustgeogen: Scalable and formal-verified data engine for trustworthy multi-modal geometric problem solving.arXiv preprint arXiv:2504.15780, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:47.648803Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:1f080b702068994f0027c48aea0548fbfbadff49227051fa866953f45432af42","observation_id":"611c1b96-836d-44db-b049-50ca3d94d462","resolution":{"observed_at":"2026-08-07T15:01:47.648803Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:47.729516Z","title":"Gemini deep research, 12 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:47.729516Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:61c0cf555fe7cff8b35d73b41403b08b7afe302d1c0e3c9083a9d27aa9fd413f","observation_id":"fcd707f8-e676-4686-9bb4-d6a9124266a5","resolution":{"observed_at":"2026-08-07T15:01:47.729516Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-08-15T12:33:55.451951Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-07T15:01:47.778287Z","title":"Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning.arXiv preprint arXiv:2501.12948, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:47.778287Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:112fc029b7a53ef27c1c979cf6a0b35a02ae2b6c6238014f1479dbfd6a36e1b9","observation_id":"3e22bf9b-4a03-4e83-b702-465daa1c6931","resolution":{"observed_at":"2026-08-07T15:01:47.778287Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2011.01060","last_updated":"2020-11-12T07:47:48Z","snapshot_observed_at":"2026-08-14T05:50:17.249446Z","submitted_at":"2020-11-02T15:42:40Z","title":"Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2011.01060","snapshot_observed_at":"2026-08-07T15:01:47.840206Z","title":"Constructing a multi-hop qa dataset for comprehensive evaluation of reasoning steps.arXiv preprint arXiv:2011.01060, 2020","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:47.840206Z"},"links":{"cited_paper":"/paper/2011.01060","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:1f66e8089488e09bc1cbdda12bf9c401bf8c7258f0429ae47df1eedb7a63765c","observation_id":"215e9b38-a1b0-4bc7-9897-9dd826d031a4","resolution":{"observed_at":"2026-08-07T15:01:47.840206Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00352","last_updated":"2024-11-01T14:36:52Z","snapshot_observed_at":"2026-08-12T16:02:21.969968Z","submitted_at":"2023-08-01T07:49:10Z","title":"MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.00352","snapshot_observed_at":"2026-08-07T15:01:47.901985Z","title":"Metagpt: Meta programming for multi-agent collaborative framework.arXiv preprint arXiv:2308.00352, 3(4):6, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:47.901985Z"},"links":{"cited_paper":"/paper/2308.00352","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:5344396ca8a7adb93136422ed42104f5ec194225c48898a2dca40ff1d976bf50","observation_id":"091d1d25-1cfe-45d9-bb4b-b1a114b9610a","resolution":{"observed_at":"2026-08-07T15:01:47.901985Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08582","last_updated":"2024-07-24T12:25:17Z","snapshot_observed_at":"2026-08-21T16:22:14.101387Z","submitted_at":"2023-10-12T17:59:50Z","title":"Tree-Planner: Efficient Close-loop Task Planning with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08582","snapshot_observed_at":"2026-08-07T15:01:47.987757Z","title":"Tree-planner: Efficient close-loop task planning with large language models.arXiv preprint arXiv:2310.08582, 2023","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:47.987757Z"},"links":{"cited_paper":"/paper/2310.08582","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:c919cf8c8e29055bbc32582cdbc92f91aac23a2439022e13ef812d9dd411c44d","observation_id":"402cca18-7e9a-4141-919a-75d7735f7b4d","resolution":{"observed_at":"2026-08-07T15:01:47.987757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:48.094720Z","title":"A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.ACM Transactions on Information Systems, 43(2):1– 55, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:48.094720Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:6809c4530000620521330770e14852b343731d049aa72ed2f8fc268e480562fd","observation_id":"30975c1a-0dd9-4284-9292-78b8f6e5bfbb","resolution":{"observed_at":"2026-08-07T15:01:48.094720Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21276","last_updated":"2024-10-25T17:43:01Z","snapshot_observed_at":"2026-08-15T14:02:47.366139Z","submitted_at":"2024-10-25T17:43:01Z","title":"GPT-4o System Card","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.21276","snapshot_observed_at":"2026-08-07T15:01:48.219960Z","title":"Gpt-4o system card.arXiv preprint arXiv:2410.21276, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:48.219960Z"},"links":{"cited_paper":"/paper/2410.21276","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:b9b07f78993068edd166e6c8316aeca69dd7603644274db1b2819ce8a78d2172","observation_id":"ee9623c0-c286-452b-b653-c596b2ab5b07","resolution":{"observed_at":"2026-08-07T15:01:48.219960Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.07758","last_updated":"2024-06-05T03:37:35Z","snapshot_observed_at":"2026-08-20T20:26:44.898724Z","submitted_at":"2023-08-15T13:19:59Z","title":"Forward-Backward Reasoning in Large Language Models for Mathematical Verification","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.07758","snapshot_observed_at":"2026-08-07T15:01:48.297471Z","title":"Forward-backward reasoning in large language models for mathematical verification.arXiv preprint arXiv:2308.07758, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:48.297471Z"},"links":{"cited_paper":"/paper/2308.07758","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:a03474723f66b1d67f1253a12a69a730a903478676927ea1c3560fadd811b9d6","observation_id":"778d78e5-c897-4141-8747-e552d25c98e1","resolution":{"observed_at":"2026-08-07T15:01:48.297471Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06770","last_updated":"2024-11-11T23:05:04Z","snapshot_observed_at":"2026-08-18T08:11:45.716032Z","submitted_at":"2023-10-10T16:47:29Z","title":"SWE-bench: Can Language Models Resolve Real-World GitHub Issues?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06770","snapshot_observed_at":"2026-08-07T15:01:48.380961Z","title":"Swe-bench: Can language models resolve real-world github issues?arXiv preprint arXiv:2310.06770, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:48.380961Z"},"links":{"cited_paper":"/paper/2310.06770","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:8d6af19d42e764714714177f47b3bb4b06b344f6e577ebc9cd5c08b077de1e8f","observation_id":"cc0ce0bd-8652-41a5-a22b-9522ea2343f6","resolution":{"observed_at":"2026-08-07T15:01:48.380961Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.09516","last_updated":"2025-08-05T19:08:38Z","snapshot_observed_at":"2026-08-15T13:17:00.526689Z","submitted_at":"2025-03-12T16:26:39Z","title":"Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.09516","snapshot_observed_at":"2026-08-07T15:01:48.462784Z","title":"Search-r1: Training llms to reason and leverage search engines with reinforcement learning.arXiv preprint arXiv:2503.09516, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:48.462784Z"},"links":{"cited_paper":"/paper/2503.09516","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:3ccf4f5170ab6b110c4247d0f92b8f4143f6cc11c9261a0b3197c7676896331c","observation_id":"43f068dc-332d-473c-8bfc-37d6d4caaa07","resolution":{"observed_at":"2026-08-07T15:01:48.462784Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1705.03551","last_updated":"2017-05-13T21:12:37Z","snapshot_observed_at":"2026-08-13T08:58:47.096400Z","submitted_at":"2017-05-09T21:35:07Z","title":"TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.03551","snapshot_observed_at":"2026-08-07T15:01:48.529406Z","title":"Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension.arXiv preprint arXiv:1705.03551, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:48.529406Z"},"links":{"cited_paper":"/paper/1705.03551","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:c86a62e444d24936dd32af88134b74e208680963b658a44ce5b795ab293eb09f","observation_id":"0e74f23f-ece1-4f61-8bbf-a13b8a87a01a","resolution":{"observed_at":"2026-08-07T15:01:48.529406Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:48.624021Z","title":"Reinforcement learning: A survey","venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:48.624021Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:c955aff66e30fa99fbc171c88b06465e7365adfee21f804a9fca7978a72a2509","observation_id":"9c5cb148-d9b7-434d-a74f-7f6fe8c99e51","resolution":{"observed_at":"2026-08-07T15:01:48.624021Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:48.710088Z","title":"Dense passage retrieval for open-domain question answering","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:48.710088Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:dcfc661dc1977e12cf133774008c5d3aeb57f46c92b295211df3f8cf8eee944f","observation_id":"1721a036-de9d-4a52-b495-ccef6511a74d","resolution":{"observed_at":"2026-08-07T15:01:48.710088Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.13648","last_updated":"2025-05-21T06:46:51Z","snapshot_observed_at":"2026-08-16T12:57:01.225261Z","submitted_at":"2025-02-19T11:49:23Z","title":"UniKnow: A Unified Framework for Reliable Language Model Behavior across Parametric and External Knowledge","version":2},"cited_work":{"arxiv_id":"2502.13648","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.13648","snapshot_observed_at":"2026-08-07T15:01:59.769238Z","title":"UniKnow: A Unified Framework for Reliable Language Model Behavior across Parametric and External Knowledge","venue":"cs.CL","work_id":"515005c8-0965-44a5-8daf-5321a9c627d3","year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:48.786022Z"},"links":{"cited_paper":"/paper/2502.13648","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:b5ff684c4eefcfbecf6952ca7f54f3d7a52ce54bb61625e491c3b8ba2de90687","observation_id":"c813b869-2e47-46b7-aae0-eb56fdaa6954","resolution":{"observed_at":"2026-08-07T15:01:59.854455Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:48.869272Z","title":"The hungarian method for the assignment problem.Naval research logistics quarterly, 2(1-2):83–97, 1955","venue":null,"work_id":null,"year":1955},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:48.869272Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:497dbc86e2e2823237f50379b5fbb2ab0a1a50b6a2eba10711b8ea12792d64cd","observation_id":"594f7765-5216-41ab-b530-fe1519d8bec8","resolution":{"observed_at":"2026-08-07T15:01:48.869272Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:48.945339Z","title":"Natural questions: a benchmark for question answering research.Transactions of the Association for Computational Linguistics, 7:453–466, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:48.945339Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:b177572b3c238cbbb26e144452429fcb0ae80f901c75300ee3325af52bdfcbc3","observation_id":"034bbc83-e669-465f-9e23-4def2e38040a","resolution":{"observed_at":"2026-08-07T15:01:48.945339Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:49.045923Z","title":"Retrieval-augmented generation for knowledge- intensive nlp tasks.Advances in neural information processing systems, 33:9459–9474, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:49.045923Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:cd6e06712b83a21ec04426771a89f5c5fcb29028dc160997c51e1e8735a7ecf1","observation_id":"63316094-82aa-4f62-af96-c6683c9dc7df","resolution":{"observed_at":"2026-08-07T15:01:49.045923Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:49.127651Z","title":"Camel: Commu- nicative agents for\" mind\" exploration of large language model society.Advances in Neural Information Processing Systems, 36:51991–52008, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:49.127651Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:836870834997cce564c146b186a7ad2a460d012e3eeecce7f0ec044b72bd4a16","observation_id":"5b2c346c-50d5-4e55-9ec6-ef2be37bfa1b","resolution":{"observed_at":"2026-08-07T15:01:49.127651Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.07316","last_updated":"2025-05-21T13:38:27Z","snapshot_observed_at":"2026-08-16T15:36:15.556886Z","submitted_at":"2025-02-11T07:26:50Z","title":"CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.07316","snapshot_observed_at":"2026-08-07T15:01:49.182311Z","title":"Codei/o: Condensing reasoning patterns via code input-output prediction.arXiv preprint arXiv:2502.07316, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:49.182311Z"},"links":{"cited_paper":"/paper/2502.07316","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:1d934837d8e475c6713b9e1573ea2f20b47583f65fe7fb0e2e2b1d744558e9c9","observation_id":"14a1550f-da7e-4db8-9338-afef52d85c5c","resolution":{"observed_at":"2026-08-07T15:01:49.182311Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05366","last_updated":"2025-01-09T16:48:17Z","snapshot_observed_at":"2026-08-15T17:19:59.096854Z","submitted_at":"2025-01-09T16:48:17Z","title":"Search-o1: Agentic Search-Enhanced Large Reasoning Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05366","snapshot_observed_at":"2026-08-07T15:01:49.281298Z","title":"Search-o1: Agentic search-enhanced large reasoning models.arXiv preprint arXiv:2501.05366, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:49.281298Z"},"links":{"cited_paper":"/paper/2501.05366","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:6988e9411c2178d4c60acb6a73ae4cdba9b7f20c02e1a6429df8e7789844f8c9","observation_id":"b62c9527-997b-4ad2-bf7e-6e0659191ad2","resolution":{"observed_at":"2026-08-07T15:01:49.281298Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:49.363237Z","title":"Openmanus: An open-source framework for building general ai agents.https://github.com/mannaandpoem/OpenManus, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:49.363237Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:b044e55bc7debb21a305df8d9316be2b6871d5586586b75c045e0746ada6f742","observation_id":"690493bc-5bc7-488a-b952-f95873eb618e","resolution":{"observed_at":"2026-08-07T15:01:49.363237Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.19437","last_updated":"2025-02-18T17:26:38Z","snapshot_observed_at":"2026-08-18T18:18:37.449517Z","submitted_at":"2024-12-27T04:03:16Z","title":"DeepSeek-V3 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.19437","snapshot_observed_at":"2026-08-07T15:01:49.481404Z","title":"Deepseek-v3 technical report.arXiv preprint arXiv:2412.19437, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:49.481404Z"},"links":{"cited_paper":"/paper/2412.19437","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:96070d74a78a55a4b773e08472192e0150756d95772be4d45111c8488db09dae","observation_id":"1996600a-f76b-45c9-9de2-996dbd426c05","resolution":{"observed_at":"2026-08-07T15:01:49.481404Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:49.582252Z","title":"Inference- time scaling for generalist reward modeling.arXiv preprint arXiv:2504.02495, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:49.582252Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:6d1cb369a728b5717800e92c23f0fa93a9d887753609f1be983b4d70316a8088","observation_id":"78f6a0db-2198-4338-9e9f-76dd49a2269c","resolution":{"observed_at":"2026-08-07T15:01:49.582252Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.21460","last_updated":"2025-03-27T12:50:17Z","snapshot_observed_at":"2026-07-06T20:59:35.694800Z","submitted_at":"2025-03-27T12:50:17Z","title":"Large Language Model Agent: A Survey on Methodology, Applications and Challenges","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.21460","snapshot_observed_at":"2026-08-07T15:01:49.684485Z","title":"Large language model agent: A survey on methodology, applications and challenges.arXiv preprint arXiv:2503.21460, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:49.684485Z"},"links":{"cited_paper":"/paper/2503.21460","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:fdb8aa5af40ea33eebfef899f45b50f177d2c5058189d34cb6674a7cb2bcdbca","observation_id":"a72772db-d49b-47f5-8a58-b276f70d5e69","resolution":{"observed_at":"2026-08-07T15:01:49.684485Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.10511","last_updated":"2023-07-02T07:21:59Z","snapshot_observed_at":"2026-07-06T14:33:08.041820Z","submitted_at":"2022-12-20T18:30:15Z","title":"When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.10511","snapshot_observed_at":"2026-08-07T15:01:49.810326Z","title":"When not to trust language models: Investigating effectiveness of parametric and non-parametric memories","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:49.810326Z"},"links":{"cited_paper":"/paper/2212.10511","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:3dd935cc774277510875fdc209aad1eccd7a0b73def56f20ed26722c03e9a038","observation_id":"42ab3d9d-addf-4c42-9d29-53c4ac9612d7","resolution":{"observed_at":"2026-08-07T15:01:49.810326Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:49.933428Z","title":"Gaia: a benchmark for general ai assistants","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:49.933428Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:501494cb3774917b78096b3ba7201a602246ee6e696759583cbe18724bec5e9b","observation_id":"644dd034-b6b8-4e11-98b2-777d9925284b","resolution":{"observed_at":"2026-08-07T15:01:49.933428Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:50.046157Z","title":"Deep research system card","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:50.046157Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:10d0ce7487e81c1e457ff620815a4bb3719c68ff37faba776229200aa82ae0dd","observation_id":"8f228cc7-3e22-4f73-b311-848da86558d1","resolution":{"observed_at":"2026-08-07T15:01:50.046157Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:50.131402Z","title":"Memgpt: Towards llms as operating systems","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:50.131402Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:431fd766b60f6d389f6f8b3ecab0d1aae06f55d2b17507dacf21091d5bef3961","observation_id":"4dcb5c48-c56d-4d57-9016-a181337a6cd2","resolution":{"observed_at":"2026-08-07T15:01:50.131402Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.03671","last_updated":"2025-05-28T05:08:18Z","snapshot_observed_at":"2026-08-13T22:18:26.874624Z","submitted_at":"2025-02-05T23:31:39Z","title":"Advancing Reasoning in Large Language Models: Promising Methods and Approaches","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.03671","snapshot_observed_at":"2026-08-07T15:01:50.206014Z","title":"Advancing reasoning in large language models: Promising methods and approaches.arXiv preprint arXiv:2502.03671, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:50.206014Z"},"links":{"cited_paper":"/paper/2502.03671","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:caad8800ca3a492e92884bab639089af236c713820db4e882f1ec3b7bc4f6c43","observation_id":"e39f4fee-a022-4cf9-9a31-14ded47c1835","resolution":{"observed_at":"2026-08-07T15:01:50.206014Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.12813","last_updated":"2023-03-08T23:41:49Z","snapshot_observed_at":"2026-08-16T13:28:02.541688Z","submitted_at":"2023-02-24T18:48:43Z","title":"Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.12813","snapshot_observed_at":"2026-08-07T15:01:50.298572Z","title":"Check your facts and try again: Improving large language models with external knowledge and automated feedback.arXiv preprint arXiv:2302.12813, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:50.298572Z"},"links":{"cited_paper":"/paper/2302.12813","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:8c68a8ea33466a267f6b16718ffeab0f6571da606a6fff44b202b0a40ba500ea","observation_id":"a6cbe681-2e65-48f0-b8c9-6a6e3271f3d4","resolution":{"observed_at":"2026-08-07T15:01:50.298572Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.03350","last_updated":"2023-10-17T18:57:17Z","snapshot_observed_at":"2026-08-21T16:05:02.584580Z","submitted_at":"2022-10-07T06:50:23Z","title":"Measuring and Narrowing the Compositionality Gap in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.03350","snapshot_observed_at":"2026-08-07T15:01:50.399671Z","title":"Measuring and narrowing the compositionality gap in language models.arXiv preprint arXiv:2210.03350, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:50.399671Z"},"links":{"cited_paper":"/paper/2210.03350","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:f825a4a8770645dc2c86d65951764ccd55c60b3ce24c61ba1c5e00b9acc8d6de","observation_id":"bc5c113b-88cc-4f32-be09-c995dd129c73","resolution":{"observed_at":"2026-08-07T15:01:50.399671Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.13068","last_updated":"2024-03-14T08:15:27Z","snapshot_observed_at":"2026-08-21T13:56:41.647275Z","submitted_at":"2023-05-22T14:37:05Z","title":"Making Language Models Better Tool Learners with Execution Feedback","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.13068","snapshot_observed_at":"2026-08-07T15:01:50.527055Z","title":"Making language models better tool learners with execution feedback.arXiv preprint arXiv:2305.13068, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:50.527055Z"},"links":{"cited_paper":"/paper/2305.13068","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:ebdcfb3fa7f829593c18b718cf367afa1e803efbbd2998fed6b1cb0147fb9268","observation_id":"ce5848bb-bb7a-4e77-9104-29c7483ecce3","resolution":{"observed_at":"2026-08-07T15:01:50.527055Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.16789","last_updated":"2023-10-03T14:45:48Z","snapshot_observed_at":"2026-08-16T04:18:30.717622Z","submitted_at":"2023-07-31T15:56:53Z","title":"ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.16789","snapshot_observed_at":"2026-08-07T15:01:50.657302Z","title":"Toolllm: Facilitating large language models to master 16000+ real-world apis.arXiv preprint arXiv:2307.16789, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:50.657302Z"},"links":{"cited_paper":"/paper/2307.16789","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:6f515c09176ae93d56fbde05121d17ddeec822e6155ed4c0be9f544daa652f53","observation_id":"19ff8281-4890-4dae-b72b-568dc585149d","resolution":{"observed_at":"2026-08-07T15:01:50.657302Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03300","last_updated":"2024-04-27T15:25:53Z","snapshot_observed_at":"2026-08-06T14:58:42.911363Z","submitted_at":"2024-02-05T18:55:32Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.03300","snapshot_observed_at":"2026-08-07T15:01:50.767884Z","title":"Deepseekmath: Pushing the limits of mathematical reasoning in open language models.arXiv preprint arXiv:2402.03300, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:50.767884Z"},"links":{"cited_paper":"/paper/2402.03300","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:1c9d8c9f41abefdc5fc9f436ae94e5d320841daa4624d4e62a0ca4f5490afb2b","observation_id":"bf577efc-4b7e-4bfe-b9c9-39ac2b2939e3","resolution":{"observed_at":"2026-08-07T15:01:50.767884Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.05592","last_updated":"2025-03-18T08:32:24Z","snapshot_observed_at":"2026-08-15T04:19:26.319323Z","submitted_at":"2025-03-07T17:14:44Z","title":"R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.05592","snapshot_observed_at":"2026-08-07T15:01:50.849688Z","title":"R1-searcher: Incentivizing the search capability in llms via reinforcement learning.arXiv preprint arXiv:2503.05592, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:50.849688Z"},"links":{"cited_paper":"/paper/2503.05592","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:905a302ded76d3fa8581d9be522f612379ba443c7e6c58902c61cfcde501f1f2","observation_id":"8e3cd2d2-d47c-486e-8c7b-6f55f1e00139","resolution":{"observed_at":"2026-08-07T15:01:50.849688Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:50.920286Z","title":"Reinforcement learning.Journal of Cognitive Neuroscience, 11(1):126–134, 1999","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:50.920286Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:7e4fb1033f23b0bc9420e0d9afc8eab57eabe72ecb69c0969e31fa66e7eb369d","observation_id":"2ca20240-bad4-4ae2-836d-25b4c2f87e5a","resolution":{"observed_at":"2026-08-07T15:01:50.920286Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.10509","last_updated":"2023-06-23T00:59:13Z","snapshot_observed_at":"2026-08-15T17:29:02.957931Z","submitted_at":"2022-12-20T18:26:34Z","title":"Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.10509","snapshot_observed_at":"2026-08-07T15:01:51.029031Z","title":"Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions.arXiv preprint arXiv:2212.10509, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:51.029031Z"},"links":{"cited_paper":"/paper/2212.10509","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:992ddce7875fe9bcdd6a859966c29e0a6bfef2a4aba3d29cbd58783463d3576b","observation_id":"793f0e73-9947-453d-a3db-c08a1840bce5","resolution":{"observed_at":"2026-08-07T15:01:51.029031Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:51.104525Z","title":"Musique: Multihop questions via single-hop question composition.Transactions of the Association for Computational Linguistics, 10:539–554, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:51.104525Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:ff7682a46f4ca120d2dd7e7cf56ddf9f024df2c59cf28c754df224c6ae0a51b5","observation_id":"b07cbbaa-7ea3-4238-a693-d612dc3b5cf9","resolution":{"observed_at":"2026-08-07T15:01:51.104525Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:51.175924Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:51.175924Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:b9d19284e3f1b9086814310575208cf5ebaa61c12b2aa36d3f2c3838e880fdb9","observation_id":"0ad1b616-83f9-481b-81fd-ca21f09f70e0","resolution":{"observed_at":"2026-08-07T15:01:51.175924Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.04091","last_updated":"2023-05-26T07:06:48Z","snapshot_observed_at":"2026-08-15T11:15:42.066340Z","submitted_at":"2023-05-06T16:34:37Z","title":"Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.04091","snapshot_observed_at":"2026-08-07T15:01:51.271476Z","title":"Plan- and-solve prompting: Improving zero-shot chain-of-thought reasoning by large language models.arXiv preprint arXiv:2305.04091, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:51.271476Z"},"links":{"cited_paper":"/paper/2305.04091","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:6d20800c51b88ad8f847fcc2fc52ad674aaf5acb162ead96057891fa3029d531","observation_id":"bd95d930-e731-475a-bfb7-c993d4cd4372","resolution":{"observed_at":"2026-08-07T15:01:51.271476Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.03533","last_updated":"2024-02-22T06:21:51Z","snapshot_observed_at":"2026-07-06T14:27:46.217000Z","submitted_at":"2022-12-07T09:25:54Z","title":"Text Embeddings by Weakly-Supervised Contrastive Pre-training","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.03533","snapshot_observed_at":"2026-08-07T15:01:51.378790Z","title":"Text embeddings by weakly-supervised contrastive pre-training.arXiv preprint arXiv:2212.03533, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:51.378790Z"},"links":{"cited_paper":"/paper/2212.03533","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:1eb839508c7a2158498680c5693f8302e440e1bbd4ca25fe2a31cd0c87790a06","observation_id":"02ed0be0-a863-4c51-95ca-6be3163ba623","resolution":{"observed_at":"2026-08-07T15:01:51.378790Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:51.518537Z","title":"Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers.Advances in neural information processing systems, 33:5776–5788, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:51.518537Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:e28b96feaf2c3a260b0bb2bfee482b02f86b06f12a91cf0248f1757727bf306b","observation_id":"814c6b55-cf7d-46bb-abbb-401c702343b2","resolution":{"observed_at":"2026-08-07T15:01:51.518537Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.11171","last_updated":"2023-03-07T17:57:37Z","snapshot_observed_at":"2026-08-16T01:49:22.176843Z","submitted_at":"2022-03-21T17:48:52Z","title":"Self-Consistency Improves Chain of Thought Reasoning in Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.11171","snapshot_observed_at":"2026-08-07T15:01:51.615429Z","title":"Self-consistency improves chain of thought reasoning in language models.arXiv preprint arXiv:2203.11171, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:51.615429Z"},"links":{"cited_paper":"/paper/2203.11171","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:8aa1eeeb6935ebe6f3de9261967ed93fc4ef8aadf838839253bdca8a4ca2d998","observation_id":"cb219b6d-eefa-4626-9778-7d0db03f3079","resolution":{"observed_at":"2026-08-07T15:01:51.615429Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:51.707303Z","title":"Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:51.707303Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:368e2eb7586d7c732d3036c8c81a443729b1f42635737ebfd97cad1ffcb187a9","observation_id":"8fa0c1b0-5eed-48b7-a3a9-731c882e894f","resolution":{"observed_at":"2026-08-07T15:01:51.707303Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:51.779425Z","title":"Avatar: Optimizing llm agents for tool usage via contrastive reasoning.Advances in Neural Information Processing Systems, 37:25981–26010, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:51.779425Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:c3280708f44e2e2d47c68c5293309147fb8a3af9bf2570c818a71dd1df4480f6","observation_id":"b1af11d8-dcda-4a62-919a-e7f7233e29b7","resolution":{"observed_at":"2026-08-07T15:01:51.779425Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:51.868860Z","title":"Omnithink: Expanding knowledge boundaries in machine writing through thinking.arXiv preprint arXiv:2501.09751, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:51.868860Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:15bc600159c9c8a8ac0fcca4b165c48a6b19a77cde01327d9a43feaea16eb821","observation_id":"4067dd1a-013e-44d5-8404-6e922c0743b0","resolution":{"observed_at":"2026-08-07T15:01:51.868860Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.14333","last_updated":"2024-05-23T09:03:42Z","snapshot_observed_at":"2026-08-16T13:50:18.721796Z","submitted_at":"2024-05-23T09:03:42Z","title":"DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.14333","snapshot_observed_at":"2026-08-07T15:01:51.945284Z","title":"Deepseek-prover: Advancing theorem proving in llms through large-scale synthetic data","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:51.945284Z"},"links":{"cited_paper":"/paper/2405.14333","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:85ae996c3be03c8578f0f6b527337ba5984e8981ab6dcc0d72994abf42926afb","observation_id":"4207c2aa-10d7-4cc2-b57f-24ee7365f39b","resolution":{"observed_at":"2026-08-07T15:01:51.945284Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-08-17T18:50:07.059564Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-07T15:01:52.044882Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:52.044882Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:f71ef07f839d1b18fc34c43bf19deef74cdceddbb116333876ee1c4a00d31d15","observation_id":"f442aaf3-56ec-4faa-a2c4-b336f64ab9ee","resolution":{"observed_at":"2026-08-07T15:01:52.044882Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:52.132950Z","title":"Gpt4tools: Teaching large language model to use tools via self-instruction.Advances in Neural Information Processing Systems, 36:71995–72007, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:52.132950Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:33da2c00818dbdd0ea830ff2de072134ee1ee840493346e2d19358db610c0eec","observation_id":"2a864e78-38ee-450c-a45f-a93d33d58a88","resolution":{"observed_at":"2026-08-07T15:01:52.132950Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.09600","last_updated":"2018-09-25T17:28:20Z","snapshot_observed_at":"2026-08-17T01:54:11.006899Z","submitted_at":"2018-09-25T17:28:20Z","title":"HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.09600","snapshot_observed_at":"2026-08-07T15:01:52.183621Z","title":"Hotpotqa: A dataset for diverse, explainable multi-hop question answering.arXiv preprint arXiv:1809.09600, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:52.183621Z"},"links":{"cited_paper":"/paper/1809.09600","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:430c5a3f952b6aa77658a921f289ca89e9099d86723c803e63fd2b4525da41a0","observation_id":"72d31ea5-a9ca-49a2-85ef-cd0c72e8b173","resolution":{"observed_at":"2026-08-07T15:01:52.183621Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:52.258691Z","title":"Tree of thoughts: Deliberate problem solving with large language models.Advances in neural information processing systems, 36:11809–11822, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:52.258691Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:9fb8dee6d9a5beab8c689808274c553db74599d12f230fbc0b467b52983151ad","observation_id":"f10a572c-bac7-48fd-9f68-d105f0286360","resolution":{"observed_at":"2026-08-07T15:01:52.258691Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:52.356651Z","title":"Re- act: Synergizing reasoning and acting in language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:52.356651Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:4141f0300ede7503885ef8caa65a974ad8f82d6838ba20b663ef72711d33b871","observation_id":"03b5cb72-3240-42fc-a5c3-9c625885ab88","resolution":{"observed_at":"2026-08-07T15:01:52.356651Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.06794","last_updated":"2023-09-13T08:33:09Z","snapshot_observed_at":"2026-08-19T16:45:22.822518Z","submitted_at":"2023-09-13T08:33:09Z","title":"Cognitive Mirage: A Review of Hallucinations in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.06794","snapshot_observed_at":"2026-08-07T15:01:52.456120Z","title":"Cognitive mirage: A review of hallucinations in large language models.arXiv preprint arXiv:2309.06794, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:52.456120Z"},"links":{"cited_paper":"/paper/2309.06794","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:4e16184f6e81ef4971b4721dceb591ebb6f3fcafb75a86bc430985e293d5ce92","observation_id":"76f415d1-231e-4d8b-bd28-b0812425b0ae","resolution":{"observed_at":"2026-08-07T15:01:52.456120Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:52.554083Z","title":"Physics of language models: Part 2.1, grade- school math and the hidden reasoning process","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:52.554083Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:d8705de18e5c63c8e10a42337ba17215ad549f1e7e501fe2298a1d73b2b95b09","observation_id":"653d0af0-7953-4fa3-a53b-b4e415f2de83","resolution":{"observed_at":"2026-08-07T15:01:52.554083Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.14476","last_updated":"2025-05-20T01:37:34Z","snapshot_observed_at":"2026-08-18T05:01:20.543826Z","submitted_at":"2025-03-18T17:49:06Z","title":"DAPO: An Open-Source LLM Reinforcement Learning System at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.14476","snapshot_observed_at":"2026-08-07T15:01:52.623494Z","title":"Dapo: An open-source llm reinforcement learning system at scale.arXiv preprint arXiv:2503.14476, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:52.623494Z"},"links":{"cited_paper":"/paper/2503.14476","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:e1b18997cd2748a04f87f55ca318f753f8d0885eb2e9b62ee57005ea9b600f8f","observation_id":"6d5116c2-3996-4605-802c-33106f2444d1","resolution":{"observed_at":"2026-08-07T15:01:52.623494Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:52.715969Z","title":"Rankrag: Unifying context ranking with retrieval-augmented generation in llms.Advances in Neural Information Processing Systems, 37:121156–121184, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:52.715969Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:88c0b7c8dd8e9274f6b0d721f0f189a19a3173b1680478134b3c261c1ee90367","observation_id":"9f508db2-4861-4a7e-b441-d4aec3024129","resolution":{"observed_at":"2026-08-07T15:01:52.715969Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.06201","last_updated":"2024-03-27T06:31:42Z","snapshot_observed_at":"2026-08-16T14:28:11.216133Z","submitted_at":"2024-01-11T15:45:11Z","title":"EASYTOOL: Enhancing LLM-based Agents with Concise Tool Instruction","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.06201","snapshot_observed_at":"2026-08-07T15:01:52.820435Z","title":"Easytool: Enhancing llm-based agents with concise tool instruction.arXiv preprint arXiv:2401.06201, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:52.820435Z"},"links":{"cited_paper":"/paper/2401.06201","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:35ad2511c962fcea19ed68991e4af2292f16d0d351339410152af391d1842f1e","observation_id":"e9f68267-02ed-43b9-b69c-8527e21d69ae","resolution":{"observed_at":"2026-08-07T15:01:52.820435Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04343","last_updated":"2025-03-02T19:44:37Z","snapshot_observed_at":"2026-08-17T04:15:37.543157Z","submitted_at":"2024-10-06T03:42:15Z","title":"Inference Scaling for Long-Context Retrieval Augmented Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04343","snapshot_observed_at":"2026-08-07T15:01:52.929152Z","title":"Inference scaling for long-context retrieval augmented generation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:52.929152Z"},"links":{"cited_paper":"/paper/2410.04343","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:16e4de66ce9bf82bd8d24af7f3e4bb3c52b437efeb265031eb4dfd4eae0a7f08","observation_id":"94d5e418-60fe-411f-8901-5df2a9f77ef0","resolution":{"observed_at":"2026-08-07T15:01:52.929152Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.03816","last_updated":"2024-11-18T05:36:16Z","snapshot_observed_at":"2026-08-19T22:24:29.848660Z","submitted_at":"2024-06-06T07:40:00Z","title":"ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.03816","snapshot_observed_at":"2026-08-07T15:01:53.041020Z","title":"Rest-mcts*: Llm self-training via process reward guided tree search, 2024a.URL https://arxiv","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:53.041020Z"},"links":{"cited_paper":"/paper/2406.03816","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:0284ecf52c31a24366462fe072f239f411ad80b00aa3293b4760fb8bcff46e3d","observation_id":"657dc109-a0cd-412b-860d-200919d6f8d1","resolution":{"observed_at":"2026-08-07T15:01:53.041020Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.01219","last_updated":"2025-09-14T09:34:46Z","snapshot_observed_at":"2026-08-16T12:38:46.158503Z","submitted_at":"2023-09-03T16:56:48Z","title":"Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.01219","snapshot_observed_at":"2026-08-07T15:01:53.124339Z","title":"Siren’s song in the ai ocean: a survey on hallucination in large language models.arXiv preprint arXiv:2309.01219, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:53.124339Z"},"links":{"cited_paper":"/paper/2309.01219","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:c02518c40959771b70babe6fe5a2e71bd3e9b67b694758a2244e9565389b53cd","observation_id":"0166a8af-3a9e-4bf1-b492-0413054aa0ef","resolution":{"observed_at":"2026-08-07T15:01:53.124339Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:53.225400Z","title":"Towards lifelong learning of large language models: A survey.ACM Computing Surveys, 57(8):1–35, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:53.225400Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:660c890c92d699ef34321f5271cc0aefb3d21dfa348a1bb52ebdfdfd63ee848c","observation_id":"f2b8f1dd-75bf-4dd2-a92a-dd8dc3af16ca","resolution":{"observed_at":"2026-08-07T15:01:53.225400Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.03160","last_updated":"2025-04-17T04:46:08Z","snapshot_observed_at":"2026-08-16T20:41:16.782304Z","submitted_at":"2025-04-04T04:41:28Z","title":"DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.03160","snapshot_observed_at":"2026-08-07T15:01:53.300843Z","title":"Deepresearcher: Scaling deep research via reinforcement learning in real-world environments.arXiv preprint arXiv:2504.03160, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:53.300843Z"},"links":{"cited_paper":"/paper/2504.03160","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:80eb0b205bf3939dbbeb8adfef93fe7a0d7c0d912a560e6633a585155635d52e","observation_id":"9d50a212-4afb-4547-a6e6-0f9653e8a99a","resolution":{"observed_at":"2026-08-07T15:01:53.300843Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.10625","last_updated":"2023-04-16T22:08:08Z","snapshot_observed_at":"2026-08-16T05:27:41.446467Z","submitted_at":"2022-05-21T15:34:53Z","title":"Least-to-Most Prompting Enables Complex Reasoning in Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.10625","snapshot_observed_at":"2026-08-07T15:01:53.399064Z","title":"Least-to-most prompting enables complex reasoning in large language models.arXiv preprint arXiv:2205.10625, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:53.399064Z"},"links":{"cited_paper":"/paper/2205.10625","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:cfdd7af987aa716f0eb4eb43f3f441a9aa52ffe7622c6b9a3d2258aa7aedabcf","observation_id":"3c9b6478-de05-4a90-9dcf-f395c8b39ed5","resolution":{"observed_at":"2026-08-07T15:01:53.399064Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.13854","last_updated":"2024-04-16T15:13:18Z","snapshot_observed_at":"2026-08-14T11:14:55.351653Z","submitted_at":"2023-07-25T22:59:32Z","title":"WebArena: A Realistic Web Environment for Building Autonomous Agents","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.13854","snapshot_observed_at":"2026-08-07T15:01:53.518376Z","title":"IND\" and","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:53.518376Z"},"links":{"cited_paper":"/paper/2307.13854","citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:63985640254260d61bc4562da2b10a53b2c90085afcab74f6fd9a8560101eeb1","observation_id":"3b763416-6090-47a8-a48f-108cead2487d","resolution":{"observed_at":"2026-08-07T15:01:53.518376Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:53.618260Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:53.618260Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:16b841f98ef349d1c75a01dbf43180e4d84490edb6593c03cc3499e058409aa6","observation_id":"7adba043-e770-4594-a863-467cceb02a30","resolution":{"observed_at":"2026-08-07T15:01:53.618260Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:53.721300Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:53.721300Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:58d9710599c0c89d6ffa1be0d9288a6e5427ebc42d9d62dc194c55010f488a5f","observation_id":"f3b28dd0-07b0-47b5-b515-efb74e773622","resolution":{"observed_at":"2026-08-07T15:01:53.721300Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:53.835103Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:53.835103Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:d18eff932b19a93e84021f787969a00a7deb50c63064da48d39d4cb093673c5d","observation_id":"4e1e5bc4-a34c-42b4-8d5c-ba06df308c3f","resolution":{"observed_at":"2026-08-07T15:01:53.835103Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:53.964131Z","title":"Key finding 1: Green energy policies have led to a 15% increase in employment across renewable energy sectors in 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:53.964131Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:3668d6810a3e18d2058e4d3d075b3ac1adcf2b174a7c8ec078044478c5eb3d78","observation_id":"f27925fd-ce24-4e7f-8360-088776a72f6d","resolution":{"observed_at":"2026-08-07T15:01:53.964131Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:01:54.082523Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:54.082523Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:ef5e57761a0965291fff15f3f5022735e19b9c8ae83d84feebf162ba07ff39fd","observation_id":"1b7069ce-8a9a-4bb9-ab59-f374f65550cd","resolution":{"observed_at":"2026-08-07T15:01:54.082523Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:07.397524Z","title":null,"venue":null,"work_id":"45c9ec9e-0206-40e8-8ff8-de420ee3626f","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:54.204923Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:2dae7241b786a6bc59b00682f7b734a972b04d27f3cb63a10f15ba7de46e9f54","observation_id":"d8b81ca9-4dbe-45e1-85f5-c3db13079f32","resolution":{"observed_at":"2026-08-07T15:02:07.471877Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:07.228240Z","title":null,"venue":null,"work_id":"756cf3d4-562c-4834-afa7-cf553fbe2e90","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:54.368152Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:4f9a91a158d2ffd4bf38d753000abb624aed78575dea042a3e5506262912e3dc","observation_id":"2e0006db-737b-4fea-bf1e-0a93d165bcc5","resolution":{"observed_at":"2026-08-07T15:02:07.316944Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:07.032632Z","title":null,"venue":null,"work_id":"71ba662d-4fa2-4448-90f3-c2b17ac40da8","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:54.503352Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:e23004eee90ded7c94357e6829d73a5d6adeec627831cb5676340f7a504a1cc0","observation_id":"c2284111-b60f-4aa1-8e1e-12575ec27185","resolution":{"observed_at":"2026-08-07T15:02:07.118479Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:06.851940Z","title":null,"venue":null,"work_id":"aeaf2d37-d5b4-4b67-962a-e3aa2336cc48","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:54.675577Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:c45b665ba0d1cda362870b70de419f1f708689714ddb00c3eef27fb712da7c0f","observation_id":"0729ce25-d2cd-48ad-bebf-0c505e88d7ff","resolution":{"observed_at":"2026-08-07T15:02:06.902036Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:06.681687Z","title":null,"venue":null,"work_id":"f38ab707-abb4-4fcf-a13e-a9676f8d817c","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:54.816652Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:0d1897bf929288f40158bdbeb13cb1b50e4785b51fd83ebe10bef4bd5a5fd782","observation_id":"925d70dc-97ac-4af9-bb18-3091e69940c4","resolution":{"observed_at":"2026-08-07T15:02:06.799178Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:06.470356Z","title":null,"venue":null,"work_id":"69e77b91-afae-4115-addf-4c345dc1587e","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:54.973379Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:7d2d6ea83448c95ee946a7b8207b8432d01b2025f9f967970229b02baca3bcc7","observation_id":"ce2a1ca1-8f55-4ccb-9599-1efefc80cfe1","resolution":{"observed_at":"2026-08-07T15:02:06.565501Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:06.272322Z","title":"Return a maximum of three distinct learnings","venue":null,"work_id":"3c50b760-9c90-45ab-817b-97b7f886940d","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:55.160156Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:d89028caca15eaefe83369d38d188231dc545e79b4a6673db4ed518e5f48bee0","observation_id":"40c6bf94-0574-4c51-a19f-7b5a86cb7c4c","resolution":{"observed_at":"2026-08-07T15:02:06.368255Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:06.112743Z","title":null,"venue":null,"work_id":"f9f4a5c9-8db7-477e-b3a4-3a20d15f795f","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:55.297085Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:a45a7e6f1da883240eee46276af3c654ca5c32ebbf70ba243ca8d7b316fe6ce6","observation_id":"1de8bf65-7cdb-44ab-bd1a-c33abc31e5b6","resolution":{"observed_at":"2026-08-07T15:02:06.175434Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:05.931255Z","title":null,"venue":null,"work_id":"f88b8a24-7a0e-49bf-8cde-690eb2b081e9","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:55.480295Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:d0f3816d034a9855ba5cd56bb8af7207faf4ddf48436e6bb38b2df7c4146eaad","observation_id":"317336d3-f42e-4078-849b-d3f4508a829e","resolution":{"observed_at":"2026-08-07T15:02:05.990506Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:05.683461Z","title":"input finding 1","venue":null,"work_id":"5f7ff7e8-648c-43a9-b727-5b0260e90e0d","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:55.614968Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:354f0fa2f8fefaf67c81c0692428a98f15f5cfae7388a0e63bb9d54b4c99b5c0","observation_id":"aefdc583-c524-4f4d-97ae-fdac0e8c431a","resolution":{"observed_at":"2026-08-07T15:02:05.832913Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:05.472697Z","title":null,"venue":null,"work_id":"0aa10fe7-fe2e-4d3e-ad17-3bc519a83cdf","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:55.751651Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:d2b859edd8df6dec431bb125aa86cd306919562418b93b793b1e7fc4bf49f009","observation_id":"19b54e8b-4aa0-4aca-9a38-d7ecf1890a12","resolution":{"observed_at":"2026-08-07T15:02:05.570165Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:05.241931Z","title":null,"venue":null,"work_id":"2e0a5f64-9dbb-49e7-bbe5-e4ce6f9ae41d","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:55.928812Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:5904a21ab0f45a272af17ef803237650a36dad2ac4395f44066aa051fa632fd6","observation_id":"69911469-f8d7-415e-b91c-04470c30f860","resolution":{"observed_at":"2026-08-07T15:02:05.354227Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:05.044100Z","title":null,"venue":null,"work_id":"d4e5f83d-e700-4d00-a5f0-b49e379bb544","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:56.057466Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:5ee120a762d7d34ffdbc35de790104386623f3d7881c8627067d545f4bb26e07","observation_id":"c010c893-8c3b-4d69-99d7-952fd0239669","resolution":{"observed_at":"2026-08-07T15:02:05.128734Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:04.884510Z","title":"Do not include any explanatory text outside the JSON array","venue":null,"work_id":"4ebe9cdd-2698-44b2-ae00-3d562b56401c","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:56.170592Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:c41b48c3c7f5921743b282d7e7c5bcbad9a02833d12bea4718694dfc1975418e","observation_id":"8a59f225-e6f4-49a4-98f2-300a79271451","resolution":{"observed_at":"2026-08-07T15:02:04.968210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:04.745367Z","title":null,"venue":null,"work_id":"4a94501b-9ad4-4e32-b7da-b5a1d13e57c0","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:56.335207Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:e8c4f19184cf86182b049826bcd0860cbad8b5216a81ff179852e06fb2b71a0b","observation_id":"cd5dc44a-6b66-4fcd-802b-762177016cdd","resolution":{"observed_at":"2026-08-07T15:02:04.813465Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:04.540517Z","title":null,"venue":null,"work_id":"d4adc8f4-eae2-4fb3-8f1d-8dcbd75e2728","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:56.513208Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:0ccdbceba004cb8734eb01ca834e690c0845a0aa4bcfd5b95006afe6f69403ff","observation_id":"7fa4c344-7704-443f-a38a-08a97526595c","resolution":{"observed_at":"2026-08-07T15:02:04.606680Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:04.364960Z","title":"O 2-Searcher is equipped with search capabilities to effectively gather and sift through pertinent online information, distilling key findings","venue":null,"work_id":"e9245773-b89a-4cb3-87c4-f3675dc5214e","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:56.624751Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:f7465e3b92e28755acae2e6c76ad28a9aa6ce2c3bc6a6b64ee26861a2aacf0ef","observation_id":"10f4ab2d-bffe-433f-a56e-bfbfd0409b53","resolution":{"observed_at":"2026-08-07T15:02:04.446765Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:04.252334Z","title":null,"venue":null,"work_id":"cce220c7-5368-415a-af48-4cfea3e54acc","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:56.690183Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:a749f9e18d8e8da4122c50efd4b1ab86e08a984f301cb74502a93e3b8746d3ca","observation_id":"38a70488-ece6-476a-9640-42227b9db57c","resolution":{"observed_at":"2026-08-07T15:02:04.286353Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:04.020650Z","title":null,"venue":null,"work_id":"14b3edac-74f5-4c61-92b2-82f46f375af3","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:56.790817Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:46042ae9950f17bbcb5ec288bde1d1a66804cfe06e0e51a88be9c1eb051ffc4c","observation_id":"938845f3-0672-43b6-b522-69cc58159b3b","resolution":{"observed_at":"2026-08-07T15:02:04.163549Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:03.796690Z","title":"Here are distilled key findings relevent to user’s query:<contents>CONTENTS</contents>","venue":null,"work_id":"693eefc6-344d-4fac-a2e9-51357d2f58ed","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:56.929816Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:2538faa5b387dcad545afcdb15e4150008be1ec3a52b79e4c62b120bd488ff25","observation_id":"9922ce81-b2b9-4650-a531-23562b18b94d","resolution":{"observed_at":"2026-08-07T15:02:03.890076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:03.550352Z","title":"Introduction","venue":null,"work_id":"3d3ba4ad-18ce-4a21-8b07-a5a74dadd17f","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:57.055868Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:af39cb6241e6184dc5c9a61fe55276655300b42b23fd6023b716644e30cb5c69","observation_id":"3fb8bc33-b64f-4b10-8b20-4243cbd2d007","resolution":{"observed_at":"2026-08-07T15:02:03.664232Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:03.354774Z","title":null,"venue":null,"work_id":"0ac39d7b-7802-4f5c-8906-ef5ae6c2f2d4","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:57.185951Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:6381dc7e779f8037cdc489e0077d8b24d8d1fc4d254b8d7c63b48546d622076b","observation_id":"ea4128f7-9e5e-4172-90ce-6bb53afedabd","resolution":{"observed_at":"2026-08-07T15:02:03.449336Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:03.214951Z","title":null,"venue":null,"work_id":"9b30f249-8a42-4ad2-a014-dc8aeefacf66","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:57.345893Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:7f207e572a198e0cd6927fc16368767e71dcea1f95040f4415b7aebedbccabf5","observation_id":"121eb02b-580b-450b-bcfe-4ca03cad9c6c","resolution":{"observed_at":"2026-08-07T15:02:03.270150Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:02:03.037049Z","title":null,"venue":null,"work_id":"cd292bcf-dfd2-40e2-909d-e77a80c0edd5","year":null},"citing_paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering","version":2},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-07T15:01:57.448378Z"},"links":{"citing_paper":"/paper/2505.16582"},"observation_digest":"sha256:a5934cca2813743962c54ad405fde8cb46b8590ce34f6730075ac51ed084a7bc","observation_id":"ae0c1e73-cadc-465d-a6d5-14d7731887dc","resolution":{"observed_at":"2026-08-07T15:02:03.139766Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.16582","last_updated":"2025-05-26T10:07:05Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-17T04:39:09.168433Z","submitted_at":"2025-05-22T12:17:13Z","title":"O$^2$-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":93,"verified_exact":1,"verified_fuzzy":6},"total_outbound_references":111},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 100 of 111 outbound references and 10 inbound Pith citation observations for arXiv:2505.16582."}