{"as_of":"2026-08-18T10:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c5e75c0a61a4f6eafb96db87b7b7b0cfc57dc0a822761375ea4e5e4a1bf2a33a","coverage":[{"denominator":46,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":46,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T08:11:22.509256Z","state":"measured"},{"denominator":46,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":46,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2601.18116/citation-record","integrity":"/paper/2601.18116/integrity","json":"/paper/2601.18116/citation-record.json","paper":"/paper/2601.18116"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T08:11:19.223922Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:19.223922Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:b77e1b952a2b8a2b960defa58911b25562458d8b696f20a801fe3f77fcaeea4d","observation_id":"8d5c9e29-4493-4daa-9984-7dd9e49d02a2","resolution":{"observed_at":"2026-08-03T08:11:19.223922Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.11511","last_updated":"2023-10-17T18:18:32Z","snapshot_observed_at":"2026-08-12T20:38:07.563701Z","submitted_at":"2023-10-17T18:18:32Z","title":"Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.11511","snapshot_observed_at":"2026-08-03T08:11:19.300589Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:19.300589Z"},"links":{"cited_paper":"/paper/2310.11511","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:06242f194b389a2f0ba686fa3e366c368b6b1a3184ac97578b351ff4ad72bacb","observation_id":"31fa7b9d-1938-4a48-8e45-969beef9cca3","resolution":{"observed_at":"2026-08-03T08:11:19.300589Z","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":"2026-08-03T08:11:19.371588Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:19.371588Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:d9e94dbd958e0694fb74179643089031bf8a3953dd1b1613a98386a13f7dca25","observation_id":"fe6f53fa-47ed-4600-976b-694be2e53a48","resolution":{"observed_at":"2026-08-03T08:11:19.371588Z","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":"2026-08-03T08:11:19.473117Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:19.473117Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:474af3e3ad13fbdef745264d69fce2df23fb7d4e38063465637b384fec5bc3f4","observation_id":"e70815d4-f0eb-426f-ba1d-ffc4c40331c1","resolution":{"observed_at":"2026-08-03T08:11:19.473117Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.06600","last_updated":"2025-08-08T17:55:11Z","snapshot_observed_at":"2026-08-16T19:56:18.562519Z","submitted_at":"2025-08-08T17:55:11Z","title":"BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agent","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.06600","snapshot_observed_at":"2026-08-03T08:11:19.646546Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:19.646546Z"},"links":{"cited_paper":"/paper/2508.06600","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:809894772dc71435a3d56b87c22f4caccec50f655e3125708bbd0a16e25de16f","observation_id":"cfc882c9-ce71-4af8-b25a-d7103f511436","resolution":{"observed_at":"2026-08-03T08:11:19.646546Z","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":"2026-08-03T08:11:19.740299Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:19.740299Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:323d939560b21d63b26de06db962225beb44c784c76402f7ac4f5aab81758fa0","observation_id":"434a244e-fcd6-4323-a7a1-b52fdb386aeb","resolution":{"observed_at":"2026-08-03T08:11:19.740299Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.16130","last_updated":"2025-02-19T10:49:41Z","snapshot_observed_at":"2026-08-16T12:38:40.131901Z","submitted_at":"2024-04-24T18:38:11Z","title":"From Local to Global: A Graph RAG Approach to Query-Focused Summarization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.16130","snapshot_observed_at":"2026-08-03T08:11:19.823833Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:19.823833Z"},"links":{"cited_paper":"/paper/2404.16130","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:4fb9a9885caa4df7597df7ad2c0b8a54cfddbcd9a15d25ab69126915679a44b5","observation_id":"7fbf5e09-8ab9-4e8b-8ddb-dc0d2e1f3faf","resolution":{"observed_at":"2026-08-03T08:11:19.823833Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.10496","last_updated":"2022-12-20T18:09:52Z","snapshot_observed_at":"2026-08-18T06:38:59.553305Z","submitted_at":"2022-12-20T18:09:52Z","title":"Precise Zero-Shot Dense Retrieval without Relevance Labels","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.10496","snapshot_observed_at":"2026-08-03T08:11:19.906474Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:19.906474Z"},"links":{"cited_paper":"/paper/2212.10496","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:b375fcfae2a8d43ca37474dd6d83ddc011fc6e7b79ccdb20302623d4ecfd0eb9","observation_id":"6f489def-ce87-4f7b-9d58-ce18259902eb","resolution":{"observed_at":"2026-08-03T08:11:19.906474Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.10997","last_updated":"2024-03-27T09:16:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-18T07:47:33Z","title":"Retrieval-Augmented Generation for Large Language Models: A Survey","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.10997","snapshot_observed_at":"2026-08-03T08:11:19.991611Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:19.991611Z"},"links":{"cited_paper":"/paper/2312.10997","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:532e764c802b0385a2ea29bf2ddffa5b2088b3332889d125f05ec39800ef5437","observation_id":"df4cadb2-600c-4297-9c3a-4e26008544fc","resolution":{"observed_at":"2026-08-03T08:11:19.991611Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.05779","last_updated":"2025-04-28T17:36:27Z","snapshot_observed_at":"2026-08-17T19:08:47.565308Z","submitted_at":"2024-10-08T08:00:12Z","title":"LightRAG: Simple and Fast Retrieval-Augmented Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.05779","snapshot_observed_at":"2026-08-03T08:11:20.075749Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.075749Z"},"links":{"cited_paper":"/paper/2410.05779","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:bca180aab04178017851f3c265cc65afc3ff299e9f1846b6401e31678d09dff5","observation_id":"7dc38f87-d227-4890-aa5a-3cac9f14e8b2","resolution":{"observed_at":"2026-08-03T08:11:20.075749Z","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":"2026-08-03T08:11:20.173047Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.173047Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:7395acef5bc30c3d1753ab8d29d8681a969a160353a1163facd1b1245f55ed26","observation_id":"149f6b4a-1e64-4b06-9fae-ce0953fa761e","resolution":{"observed_at":"2026-08-03T08:11:20.173047Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.14802","last_updated":"2025-06-19T21:34:45Z","snapshot_observed_at":"2026-08-16T14:13:54.817924Z","submitted_at":"2025-02-20T18:26:02Z","title":"From RAG to Memory: Non-Parametric Continual Learning for Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.14802","snapshot_observed_at":"2026-08-03T08:11:20.314373Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.314373Z"},"links":{"cited_paper":"/paper/2502.14802","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:4cac8cb4f6b0e8bd30affa2154cd020bd0f885fef40126b0d89a8ec383607bf2","observation_id":"60628e6c-ce73-42b1-83e0-1a0c0421c820","resolution":{"observed_at":"2026-08-03T08:11:20.314373Z","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":"2026-08-03T08:11:20.262780Z","title":"InAdvances in Neural Information Processing Systems, Vol","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.262780Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:2bf30f7ae030d325e37579254eba5ebaa4ead3712e7bd729bd428e5b8bbeb761","observation_id":"f5d71482-2611-4d45-bccb-667e31416027","resolution":{"observed_at":"2026-08-03T08:11:20.262780Z","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":"2026-08-03T08:11:20.443986Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.443986Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:3461f431deea4dd976dafdcb65d16a1eec2c93b94ba85c8feb92b81401172a1b","observation_id":"31d5057e-1312-44b5-a9ac-5375f8b3a466","resolution":{"observed_at":"2026-08-03T08:11:20.443986Z","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":"2026-08-03T08:11:20.386671Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.386671Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:28c392c5aa68ae98c5780a68d3075844c2838be1249a367280200f21761a3587","observation_id":"b5de1eb4-c546-42f3-afbc-cfdb1dbca4d3","resolution":{"observed_at":"2026-08-03T08:11:20.386671Z","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":"2026-08-03T08:11:20.567581Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.567581Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:9b223ec8075cd675b1eacaa1f492d7da84cf0475a608b2a9d3e1eef66f4f19f4","observation_id":"41c00261-37e3-4562-867b-6f43d18641ba","resolution":{"observed_at":"2026-08-03T08:11:20.567581Z","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":"2026-08-03T08:11:20.495268Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.495268Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:bb59c107d12393deff7ac1e51fe2cc87faf90ab48c8a122b993ea2994fdb35e8","observation_id":"abb6c686-a5c0-42c1-a9c1-1643011fda22","resolution":{"observed_at":"2026-08-03T08:11:20.495268Z","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":"2026-08-03T08:11:20.739884Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.739884Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:17d55cb3dd07f709b12d153b7705f27cd888283caa8fa430b6f9a7ff59a5b504","observation_id":"4c720b63-6f9b-441c-95a8-0e5a29f4e801","resolution":{"observed_at":"2026-08-03T08:11:20.739884Z","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":"2026-08-03T08:11:20.799985Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.799985Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:d4ad2f6639efe35e2e2dcca2d707b0d05d487c216424794d8ef185709086068b","observation_id":"56c23290-8ad6-44e1-a7d0-81b3eaeca243","resolution":{"observed_at":"2026-08-03T08:11:20.799985Z","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":"2026-08-03T08:11:20.684047Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.684047Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:ce6130cf3aa2f7f1f8434c46a21775f76a43acade2aef7e448f8baf0dff26a04","observation_id":"8b4c7b95-9813-4afe-8f3e-1af0282e0053","resolution":{"observed_at":"2026-08-03T08:11:20.684047Z","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":"2026-08-03T08:11:20.908201Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.908201Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:c40c5d6d431194c21a5b7e3a55b955072df9ec50b1a76f8dd3e748d83ce886af","observation_id":"c2a0e2cf-774c-47f6-9a26-9eda8abbffc1","resolution":{"observed_at":"2026-08-03T08:11:20.908201Z","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":"2026-08-03T08:11:20.956986Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.956986Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:631aaea09631a04ca677005f5f4276569518db923960bf12007adbf7e56f9fe2","observation_id":"498300ed-bee6-49ac-a527-fc33f1465a5f","resolution":{"observed_at":"2026-08-03T08:11:20.956986Z","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":"2026-08-03T08:11:20.852444Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.852444Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:0d090ca559578e951848aa1710d18d830e382eefc607f1d4bc9d0c4fe3a8ca1f","observation_id":"5cc3d097-4040-418e-afd5-a27361c6cdfa","resolution":{"observed_at":"2026-08-03T08:11:20.852444Z","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":"2026-08-03T08:11:21.099730Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:21.099730Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:cdad073480c9799167508e2a0f24267bede46cae83bafbe97faa27ff0e62dd79","observation_id":"62a01deb-db51-41b5-937f-c21dc20192f9","resolution":{"observed_at":"2026-08-03T08:11:21.099730Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.10925","last_updated":"2025-08-08T19:24:38Z","snapshot_observed_at":"2026-08-14T02:46:12.121034Z","submitted_at":"2025-08-08T19:24:38Z","title":"gpt-oss-120b & gpt-oss-20b Model Card","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.10925","snapshot_observed_at":"2026-08-03T08:11:21.196459Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:21.196459Z"},"links":{"cited_paper":"/paper/2508.10925","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:51c019d737c9defc010b5a4ab394ae7747ff679f9a3fec6737e5d89a619d183b","observation_id":"f89c468f-d796-4a7f-a638-d54da5050815","resolution":{"observed_at":"2026-08-03T08:11:21.196459Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.09332","last_updated":"2022-06-01T19:08:11Z","snapshot_observed_at":"2026-08-07T17:14:39.278754Z","submitted_at":"2021-12-17T05:43:43Z","title":"WebGPT: Browser-assisted question-answering with human feedback","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.09332","snapshot_observed_at":"2026-08-03T08:11:21.041974Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:21.041974Z"},"links":{"cited_paper":"/paper/2112.09332","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:51aa83daf21d994e0668362d438002da35949486b570f1f5932be9a57338b9fa","observation_id":"c26e4909-3494-4c69-b599-3b9be6d07c01","resolution":{"observed_at":"2026-08-03T08:11:21.041974Z","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":"2026-08-03T08:11:21.377068Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:21.377068Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:ce398adaf599d0c80c75602062050abbfa53e8e281767185292851d3855e8db6","observation_id":"e39b5ce6-5303-40a1-a307-d16df5a3f044","resolution":{"observed_at":"2026-08-03T08:11:21.377068Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.05530","last_updated":"2024-12-16T17:39:39Z","snapshot_observed_at":"2026-08-14T18:15:53.516440Z","submitted_at":"2024-03-08T18:54:20Z","title":"Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.05530","snapshot_observed_at":"2026-08-03T08:11:21.441846Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:21.441846Z"},"links":{"cited_paper":"/paper/2403.05530","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:7f469631f70d6d08b8becf2263fb13911b673d2056109804c11f5e4c4a3a6701","observation_id":"77c81253-4c4a-4bb1-9d74-18ce57f9052b","resolution":{"observed_at":"2026-08-03T08:11:21.441846Z","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":"2026-08-15T17:25:43.175408Z","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":"2026-08-03T08:11:21.290333Z","title":"Smith, and Mike Lewis","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:21.290333Z"},"links":{"cited_paper":"/paper/2210.03350","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:f5281a4fd339fe075ed2917a5ea6381fad889a2a259218b09c5172465d34b453","observation_id":"417ecb10-d22c-4227-9642-3ede3accfe8c","resolution":{"observed_at":"2026-08-03T08:11:21.290333Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.04761","last_updated":"2023-02-09T16:49:57Z","snapshot_observed_at":"2026-07-06T14:50:07.491434Z","submitted_at":"2023-02-09T16:49:57Z","title":"Toolformer: Language Models Can Teach Themselves to Use Tools","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.04761","snapshot_observed_at":"2026-08-03T08:11:21.571312Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:21.571312Z"},"links":{"cited_paper":"/paper/2302.04761","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:942132dec942352030017e51a9444165c0743eb61ef63fcac11e1256d93bf850","observation_id":"c111b749-6393-46fb-ba24-f3d230ec7ac6","resolution":{"observed_at":"2026-08-03T08:11:21.571312Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.12652","last_updated":"2023-05-24T05:08:07Z","snapshot_observed_at":"2026-08-17T20:02:13.545674Z","submitted_at":"2023-01-30T04:18:09Z","title":"REPLUG: Retrieval-Augmented Black-Box Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.12652","snapshot_observed_at":"2026-08-03T08:11:21.639337Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:21.639337Z"},"links":{"cited_paper":"/paper/2301.12652","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:10661aebf89fb0e7c75a897482ef5306e43a197fcc218bcb12b8467fa761cf78","observation_id":"515b00ff-7b8b-4345-bb96-c8f4a5fb63b7","resolution":{"observed_at":"2026-08-03T08:11:21.639337Z","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":"2026-08-03T08:11:21.510776Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:21.510776Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:5ba55fe720fda68834d7e7e01aaa66685f117bb3136bb4beb704ba5f217fba7e","observation_id":"b9480ccf-c502-4286-98c1-3f7b8fc55647","resolution":{"observed_at":"2026-08-03T08:11:21.510776Z","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":"10.18653/v1/2025.findings-acl.20","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":null,"work_id":"b3d8e894-e5f5-429d-af8a-72a1a3e7ce0a","year":2025},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:21.813063Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:a7e42f4591c4603fe25f50e5a7b9661e7a224cf870c52a2faec603affcb07e4e","observation_id":"2acab878-64b8-4f70-86ca-71612a25a7cc","resolution":{"observed_at":"2026-08-03T08:13:31.715884Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.09388","last_updated":"2025-05-14T13:41:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-14T13:41:34Z","title":"Qwen3 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.09388","snapshot_observed_at":"2026-08-03T08:11:21.875785Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:21.875785Z"},"links":{"cited_paper":"/paper/2505.09388","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:6e86f8980f79c70095059f1fa2afcbdfc1c4e6337b3b428b3e6012f75339523c","observation_id":"9a8c4fbf-a05f-403e-94ac-62cfe9a0aa56","resolution":{"observed_at":"2026-08-03T08:11:21.875785Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.15391","last_updated":"2024-01-27T11:41:48Z","snapshot_observed_at":"2026-08-13T01:06:03.395715Z","submitted_at":"2024-01-27T11:41:48Z","title":"MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.15391","snapshot_observed_at":"2026-08-03T08:11:21.724695Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:21.724695Z"},"links":{"cited_paper":"/paper/2401.15391","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:52e804b6197d2571c985605f5bbb751ae5e4433c8d7d6fd0aa7fadafe8de259d","observation_id":"d0720af4-581f-4da3-9a65-e01097a7d778","resolution":{"observed_at":"2026-08-03T08:11:21.724695Z","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":"2026-08-03T08:11:22.082416Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:22.082416Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:960d107ecad7c82a0adb2fe6329cb2a245549bc885e6ccff5f45f30b7ae56dcf","observation_id":"71cbd2af-cd1b-482a-aced-0c695f292583","resolution":{"observed_at":"2026-08-03T08:11:22.082416Z","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":"2026-08-03T08:11:22.168909Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:22.168909Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:25048d14ec5ca18fadd77d44dc031a8096ec10a94db01b361c8accda0d5e8fcc","observation_id":"1134e325-f7ab-4d72-8f9f-dbdb5a30fbb6","resolution":{"observed_at":"2026-08-03T08:11:22.168909Z","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":"2026-08-03T08:11:21.933743Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:21.933743Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:21616f3d551eacfa9bec2505d9341cd382cb12978e112efd8b5383c4d58ba8ff","observation_id":"393cf5d7-3ead-4564-b45c-ffe616c4da05","resolution":{"observed_at":"2026-08-03T08:11:21.933743Z","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":"2026-08-03T08:11:22.309728Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:22.309728Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:e8e07f9e347ef8460c49143fffac6ea40d87243a4bb8429c74697e631e10cd59","observation_id":"334c0250-40af-4eaa-a993-f9ea1f15d360","resolution":{"observed_at":"2026-08-03T08:11:22.309728Z","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":"2026-08-03T08:11:22.457765Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:22.457765Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:65316475803344c7f09bf9df6384e65528ae5e2abf942b8cc01c91967823722c","observation_id":"9be0f39b-7dcc-4df2-8aec-643e262aec13","resolution":{"observed_at":"2026-08-03T08:11:22.457765Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.03629","last_updated":"2023-03-10T01:00:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-10-06T01:00:32Z","title":"ReAct: Synergizing Reasoning and Acting in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.03629","snapshot_observed_at":"2026-08-03T08:11:22.224977Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:22.224977Z"},"links":{"cited_paper":"/paper/2210.03629","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:4d05242e3918b537c3c265d78cd991c01637dd56c3e28ab02bdb22064fbe4cb9","observation_id":"8cf4890b-499c-4b0b-a1bc-661ef759ee56","resolution":{"observed_at":"2026-08-03T08:11:22.224977Z","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":"2026-08-03T08:11:22.509256Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:22.509256Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:2f65a7c0c803d0f23533c8342adef5c12f4318c796aaadabcb893fdad9215d7d","observation_id":"a2a04cda-de16-4e85-b90b-434ddfe4aac8","resolution":{"observed_at":"2026-08-03T08:11:22.509256Z","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":"2026-08-03T08:11:22.020032Z","title":"InProceedings of the 61st Annual Meeting of the Association for Computational Linguistics","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:22.020032Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:caa42c566936e3299b35a744b1a23b3321c48c8dec54956edc0f12d82675aff7","observation_id":"07944863-8528-4365-9b90-c24245125023","resolution":{"observed_at":"2026-08-03T08:11:22.020032Z","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":"2026-08-03T08:11:19.565265Z","title":"InFindings of the As- sociation for Computational Linguistics: ACL 2024, Lun-Wei Ku, Andre Martins, and Vivek Srikumar (Eds.)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:19.565265Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:94ecbf8d9680934af8f382011841cfd18fee764892b87adeac4903c77a43cf6c","observation_id":"eece8870-8414-4457-ab19-82118cf32896","resolution":{"observed_at":"2026-08-03T08:11:19.565265Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.05176","last_updated":"2025-06-11T02:54:49Z","snapshot_observed_at":"2026-08-17T07:57:12.232097Z","submitted_at":"2025-06-05T15:49:48Z","title":"Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.05176","snapshot_observed_at":"2026-08-03T08:11:22.394247Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:22.394247Z"},"links":{"cited_paper":"/paper/2506.05176","citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:f28eb0779788e38f40cda9534b5f9cccb8d440b294d84fc61188232110904a3f","observation_id":"a4f5b7f5-685a-4c34-8b02-f86e2a755692","resolution":{"observed_at":"2026-08-03T08:11:22.394247Z","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":"2026-08-03T08:11:20.622003Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning","version":2},"reference_index":3520,"source":"pdf_text","source_observed_at":"2026-08-03T08:11:20.622003Z"},"links":{"citing_paper":"/paper/2601.18116"},"observation_digest":"sha256:0a5453beb5c49c5b8a72f308e286f2de523ede237f428568105ff81b0dfa7212","observation_id":"b489590a-dc78-42ba-97d9-a8f7e658dd36","resolution":{"observed_at":"2026-08-03T08:11:20.622003Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2601.18116","last_updated":"2026-05-27T02:05:44Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-16T06:24:22.499453Z","submitted_at":"2026-01-26T04:00:56Z","title":"BEAR: Budgeted Evidence Allocation for Multi-Document Reasoning"},"reference_resolution":{"displayed":46,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":45,"verified_exact":1,"verified_fuzzy":0},"total_outbound_references":46},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2601.18116."}