{"as_of":"2026-08-10T22:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b211ae1b46ebabdaf91847a742a258f6b16514ae330745958abdc9873afce369","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T13:30:48.284662Z","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":"2026-05-17T10:23:05.125704Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.17390","last_updated":"2023-12-06T10:07:01Z","snapshot_observed_at":"2026-07-06T15:34:16.800916Z","submitted_at":"2023-05-27T07:04:15Z","title":"SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks","version":2},"cited_work":{"arxiv_id":"2305.17390","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.17390","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2305.17390 , year=","venue":null,"work_id":"a5c09705-254a-4b36-8599-2f7f74b12daa","year":2023},"citing_paper":{"arxiv_id":"2309.02427","last_updated":"2024-03-15T15:44:11Z","snapshot_observed_at":"2026-08-03T00:38:27.580701Z","submitted_at":"2023-09-05T17:56:20Z","title":"Cognitive Architectures for Language Agents","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-16T19:33:44.146134Z"},"links":{"cited_paper":"/paper/2305.17390","citing_paper":"/paper/2309.02427"},"observation_digest":"sha256:71070259c29cc290ef29aec418d76ad26ee98080d47e9e0c9ba1ea595cff28bf","observation_id":"e57c1eaa-f41d-46d5-89e7-cfb99c2627b5","resolution":{"observed_at":"2026-05-16T19:33:44.411856Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.17390","last_updated":"2023-12-06T10:07:01Z","snapshot_observed_at":"2026-07-06T15:34:16.800916Z","submitted_at":"2023-05-27T07:04:15Z","title":"SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks","version":2},"cited_work":{"arxiv_id":"2305.17390","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.17390","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2305.17390 , year=","venue":null,"work_id":"a5c09705-254a-4b36-8599-2f7f74b12daa","year":2023},"citing_paper":{"arxiv_id":"2309.07864","last_updated":"2023-09-19T08:29:18Z","snapshot_observed_at":"2026-08-09T18:54:02.679174Z","submitted_at":"2023-09-14T17:12:03Z","title":"The Rise and Potential of Large Language Model Based Agents: A Survey","version":3},"reference_index":186,"source":"pdf_text","source_observed_at":"2026-05-11T10:47:44.152066Z"},"links":{"cited_paper":"/paper/2305.17390","citing_paper":"/paper/2309.07864"},"observation_digest":"sha256:07649312ebe5301a054c5d3cdafdf68396c2ffa48c7d296a080bb54c2483b5ac","observation_id":"a89f83ef-4ac4-47e1-a712-c36080a45aa1","resolution":{"observed_at":"2026-05-11T10:47:45.372784Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.17390","last_updated":"2023-12-06T10:07:01Z","snapshot_observed_at":"2026-07-06T15:34:16.800916Z","submitted_at":"2023-05-27T07:04:15Z","title":"SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks","version":2},"cited_work":{"arxiv_id":"2305.17390","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.17390","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2305.17390 , year=","venue":null,"work_id":"a5c09705-254a-4b36-8599-2f7f74b12daa","year":2023},"citing_paper":{"arxiv_id":"2402.02716","last_updated":"2024-02-05T04:25:24Z","snapshot_observed_at":"2026-08-10T13:27:24.204831Z","submitted_at":"2024-02-05T04:25:24Z","title":"Understanding the planning of LLM agents: A survey","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-13T18:12:57.568144Z"},"links":{"cited_paper":"/paper/2305.17390","citing_paper":"/paper/2402.02716"},"observation_digest":"sha256:dff834e15c771226894979e6187bad2bb2bfb8ea779458ca46f365885c391d61","observation_id":"137a16c8-c4f0-4e24-be3c-92be947a224f","resolution":{"observed_at":"2026-05-13T18:12:57.693480Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.17390","last_updated":"2023-12-06T10:07:01Z","snapshot_observed_at":"2026-07-06T15:34:16.800916Z","submitted_at":"2023-05-27T07:04:15Z","title":"SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks","version":2},"cited_work":{"arxiv_id":"2305.17390","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.17390","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2305.17390 , year=","venue":null,"work_id":"a5c09705-254a-4b36-8599-2f7f74b12daa","year":2023},"citing_paper":{"arxiv_id":"2402.03578","last_updated":"2026-01-28T04:55:23Z","snapshot_observed_at":"2026-07-06T17:25:53.950578Z","submitted_at":"2024-02-05T23:06:42Z","title":"LLM Multi-Agent Systems: Challenges and Open Problems","version":3},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-05-17T10:23:05.028790Z"},"links":{"cited_paper":"/paper/2305.17390","citing_paper":"/paper/2402.03578"},"observation_digest":"sha256:32879b26a99c7ba9a738d1037dbd7c17f0286b8614fcfc543506bd93f1e10b1c","observation_id":"80b0324b-a514-4ec3-bd70-ec981231edeb","resolution":{"observed_at":"2026-05-17T10:23:05.128866Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.17390","last_updated":"2023-12-06T10:07:01Z","snapshot_observed_at":"2026-07-06T15:34:16.800916Z","submitted_at":"2023-05-27T07:04:15Z","title":"SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.17390","snapshot_observed_at":"2026-08-09T13:30:48.284662Z","title":"Swiftsage: A generative agent with fast and slow thinking for complex interactive tasks,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02066","last_updated":"2025-02-04T07:31:55Z","snapshot_observed_at":"2026-08-09T13:25:11.880488Z","submitted_at":"2025-02-04T07:31:55Z","title":"Anticipate & Act : Integrating LLMs and Classical Planning for Efficient Task Execution in Household Environments","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T13:30:48.284662Z"},"links":{"cited_paper":"/paper/2305.17390","citing_paper":"/paper/2502.02066"},"observation_digest":"sha256:7d6ff28be9c59d225f9782867042c0477dff1ee05c3428d974dea5aa897aa065","observation_id":"17db7ce0-2b4c-4f3a-a714-e452738ab6df","resolution":{"observed_at":"2026-08-09T13:30:48.284662Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.17390","last_updated":"2023-12-06T10:07:01Z","snapshot_observed_at":"2026-07-06T15:34:16.800916Z","submitted_at":"2023-05-27T07:04:15Z","title":"SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.17390","snapshot_observed_at":"2026-08-03T09:21:37.853241Z","title":"Swiftsage: A generative agent with fast and slow thinking for complex interactive tasks, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.14192","last_updated":"2026-07-03T11:26:58Z","snapshot_observed_at":"2026-08-07T15:05:40.772054Z","submitted_at":"2026-01-20T17:51:56Z","title":"Toward Efficient Agents: Memory, Tool learning, and Planning","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-03T09:21:37.853241Z"},"links":{"cited_paper":"/paper/2305.17390","citing_paper":"/paper/2601.14192"},"observation_digest":"sha256:c4e9d2b443c57998722ba9418fb46684aee61fb93ac5f5f62cfd1c5c65d6d03a","observation_id":"45ae83e9-3a82-4e05-909b-d4179d9b329f","resolution":{"observed_at":"2026-08-03T09:21:37.853241Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.17390","last_updated":"2023-12-06T10:07:01Z","snapshot_observed_at":"2026-07-06T15:34:16.800916Z","submitted_at":"2023-05-27T07:04:15Z","title":"SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks","version":2},"cited_work":{"arxiv_id":"2305.17390","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.17390","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2305.17390 , year=","venue":null,"work_id":"a5c09705-254a-4b36-8599-2f7f74b12daa","year":2023},"citing_paper":{"arxiv_id":"2605.06716","last_updated":"2026-05-07T03:38:48Z","snapshot_observed_at":"2026-08-02T11:07:24.826739Z","submitted_at":"2026-05-07T03:38:48Z","title":"From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-11T01:10:12.281373Z"},"links":{"cited_paper":"/paper/2305.17390","citing_paper":"/paper/2605.06716"},"observation_digest":"sha256:87540fe3377da1244e3005c09fdf4285a8722f647504c5656f1ae84e0fc93edf","observation_id":"b789b2c2-d2a6-4690-83af-1ac5381ba1e9","resolution":{"observed_at":"2026-05-11T04:40:58.906982Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.17390","last_updated":"2023-12-06T10:07:01Z","snapshot_observed_at":"2026-07-06T15:34:16.800916Z","submitted_at":"2023-05-27T07:04:15Z","title":"SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks","version":2},"cited_work":{"arxiv_id":"2305.17390","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.17390","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2305.17390 , year=","venue":null,"work_id":"a5c09705-254a-4b36-8599-2f7f74b12daa","year":2023},"citing_paper":{"arxiv_id":"2605.11376","last_updated":"2026-05-12T01:04:37Z","snapshot_observed_at":"2026-08-02T06:26:16.775922Z","submitted_at":"2026-05-12T01:04:37Z","title":"LLM-X: A Scalable Negotiation-Oriented Exchange for Communication Among Personal LLM Agents","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-13T02:50:18.095752Z"},"links":{"cited_paper":"/paper/2305.17390","citing_paper":"/paper/2605.11376"},"observation_digest":"sha256:383110697e6982db539d703adceb85e285f8506cdad45a0b4ba65018325cd495","observation_id":"de3d4c93-8a52-429a-bc78-eefb90a38560","resolution":{"observed_at":"2026-05-13T02:52:08.857967Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2305.17390/citation-record","integrity":"/paper/2305.17390/integrity","json":"/paper/2305.17390/citation-record.json","paper":"/paper/2305.17390"},"outbound":[],"paper":{"arxiv_id":"2305.17390","last_updated":"2023-12-06T10:07:01Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T15:34:16.800916Z","submitted_at":"2023-05-27T07:04:15Z","title":"SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2305.17390."}