{"as_of":"2026-08-10T01:17:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1e172b8b8cbf70e3dc4872eb6b4bdb9b52813160867e9e64d6cf892c99d2b5da","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":"2026-08-09T06:31:02.800959+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":"2026-08-07T14:40:33.302731Z","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":"2026-06-29T17:03:40.757203Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.18225","last_updated":"2024-02-28T10:43:54Z","snapshot_observed_at":"2026-08-10T00:56:39.053255Z","submitted_at":"2024-02-28T10:43:54Z","title":"CogBench: a large language model walks into a psychology lab","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.18225","snapshot_observed_at":"2026-08-07T14:40:33.302731Z","title":"Cogbench: A Large Language Model Walks into A Psychology Lab","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.17968","last_updated":"2025-05-23T14:37:36Z","snapshot_observed_at":"2026-08-09T15:44:39.451037Z","submitted_at":"2025-05-23T14:37:36Z","title":"Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T14:40:33.302731Z"},"links":{"cited_paper":"/paper/2402.18225","citing_paper":"/paper/2505.17968"},"observation_digest":"sha256:a490493880d9fdfb53170662f7518ff5813c340218c6c84bb1a6febdab693c0f","observation_id":"573ec285-8443-4393-8478-1bca2ad57f2b","resolution":{"observed_at":"2026-08-07T14:40:33.302731Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.18225","last_updated":"2024-02-28T10:43:54Z","snapshot_observed_at":"2026-08-10T00:56:39.053255Z","submitted_at":"2024-02-28T10:43:54Z","title":"CogBench: a large language model walks into a psychology lab","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.18225","snapshot_observed_at":"2026-08-07T11:00:53.463434Z","title":"Cogbench: a large language model walks into a psychology lab.arXiv preprint arXiv:2402.18225, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06366","last_updated":"2025-06-12T10:22:01Z","snapshot_observed_at":"2026-08-09T20:26:32.963470Z","submitted_at":"2025-06-04T08:12:32Z","title":"AI Agent Behavioral Science","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T11:00:53.463434Z"},"links":{"cited_paper":"/paper/2402.18225","citing_paper":"/paper/2506.06366"},"observation_digest":"sha256:4e560a5015add916ac0079b15b4cdf493b26adf8d0ae1903c7e5298a7e8dba04","observation_id":"bda32900-7291-46cc-9e6b-05664bda5087","resolution":{"observed_at":"2026-08-07T11:00:53.463434Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.18225","last_updated":"2024-02-28T10:43:54Z","snapshot_observed_at":"2026-08-10T00:56:39.053255Z","submitted_at":"2024-02-28T10:43:54Z","title":"CogBench: a large language model walks into a psychology lab","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.18225","snapshot_observed_at":"2026-08-07T05:40:48.114283Z","title":"Cogbench: a large language model walks into a psychology lab.arXiv preprint arXiv:2402.18225, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07388","last_updated":"2025-06-09T03:24:01Z","snapshot_observed_at":"2026-08-09T01:50:48.491215Z","submitted_at":"2025-06-09T03:24:01Z","title":"Shapley-Coop: Credit Assignment for Emergent Cooperation in Self-Interested LLM Agents","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:40:48.114283Z"},"links":{"cited_paper":"/paper/2402.18225","citing_paper":"/paper/2506.07388"},"observation_digest":"sha256:44c7d0645a0dcc9e9c6c59e4f3cf0b0420839649df5d000426dab133dbdc3824","observation_id":"dbc1715b-c606-4bc2-aab4-b085b66421f7","resolution":{"observed_at":"2026-08-07T05:40:48.114283Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.18225","last_updated":"2024-02-28T10:43:54Z","snapshot_observed_at":"2026-08-10T00:56:39.053255Z","submitted_at":"2024-02-28T10:43:54Z","title":"CogBench: a large language model walks into a psychology lab","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.18225","snapshot_observed_at":"2026-08-07T00:55:26.488281Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.12486","last_updated":"2025-06-14T12:54:07Z","snapshot_observed_at":"2026-08-08T00:29:36.785379Z","submitted_at":"2025-06-14T12:54:07Z","title":"DinoCompanion: An Attachment-Theory Informed Multimodal Robot for Emotionally Responsive Child-AI Interaction","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T00:55:26.488281Z"},"links":{"cited_paper":"/paper/2402.18225","citing_paper":"/paper/2506.12486"},"observation_digest":"sha256:fc486e497cbb1043563718417aa02c495d4a140737d042925ae30c4ee7c7931f","observation_id":"5ddf1cd7-846a-4ce1-8c40-07d219059245","resolution":{"observed_at":"2026-08-07T00:55:26.488281Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.18225","last_updated":"2024-02-28T10:43:54Z","snapshot_observed_at":"2026-08-10T00:56:39.053255Z","submitted_at":"2024-02-28T10:43:54Z","title":"CogBench: a large language model walks into a psychology lab","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.18225","snapshot_observed_at":"2026-08-06T20:13:25.684876Z","title":"arXiv preprint arXiv:2402.18225 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.03543","last_updated":"2025-07-04T12:50:43Z","snapshot_observed_at":"2026-08-09T14:15:17.133848Z","submitted_at":"2025-07-04T12:50:43Z","title":"H2HTalk: Evaluating Large Language Models as Emotional Companion","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T20:13:25.684876Z"},"links":{"cited_paper":"/paper/2402.18225","citing_paper":"/paper/2507.03543"},"observation_digest":"sha256:67c8d322c791ccb6cc8aa8f9b80c9adf0a9d0433e0da68073c5c5816fbc58c6e","observation_id":"5b3813b1-ca91-4230-8204-1c8b8a1f3a4d","resolution":{"observed_at":"2026-08-06T20:13:25.684876Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.18225","last_updated":"2024-02-28T10:43:54Z","snapshot_observed_at":"2026-08-10T00:56:39.053255Z","submitted_at":"2024-02-28T10:43:54Z","title":"CogBench: a large language model walks into a psychology lab","version":1},"cited_work":{"arxiv_id":"2402.18225","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.18225","snapshot_observed_at":"2026-06-29T17:03:40.757203Z","title":"X., and Schulz, E","venue":null,"work_id":"2c382c35-483d-45e7-83eb-d51483a625d2","year":2024},"citing_paper":{"arxiv_id":"2603.03295","last_updated":"2026-05-13T10:48:07Z","snapshot_observed_at":"2026-07-06T22:47:41.997192Z","submitted_at":"2026-02-06T15:39:54Z","title":"Language Model Goal Selection Differs from Humans' in a Self-Directed Learning Task","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-16T06:48:55.986272Z"},"links":{"cited_paper":"/paper/2402.18225","citing_paper":"/paper/2603.03295"},"observation_digest":"sha256:3a1d702249cea5c49c414367b871d24842635b3c11825c817375cada47cd3bf9","observation_id":"167a7d71-7455-4eff-8fa9-f52c84ffce97","resolution":{"observed_at":"2026-05-16T06:50:42.344250Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.18225","last_updated":"2024-02-28T10:43:54Z","snapshot_observed_at":"2026-08-10T00:56:39.053255Z","submitted_at":"2024-02-28T10:43:54Z","title":"CogBench: a large language model walks into a psychology lab","version":1},"cited_work":{"arxiv_id":"2402.18225","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.18225","snapshot_observed_at":"2026-06-29T17:03:40.757203Z","title":"X., and Schulz, E","venue":null,"work_id":"2c382c35-483d-45e7-83eb-d51483a625d2","year":2024},"citing_paper":{"arxiv_id":"2605.27593","last_updated":"2026-05-26T19:06:39Z","snapshot_observed_at":"2026-07-06T23:37:16.981482Z","submitted_at":"2026-05-26T19:06:39Z","title":"Voluntary Collusion with Secret Tools in Competing LLM Agents","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-29T17:01:22.732390Z"},"links":{"cited_paper":"/paper/2402.18225","citing_paper":"/paper/2605.27593"},"observation_digest":"sha256:26c3818ef39dfdc3148aa7273b7ae3b622ec9521f6a5bb28968064a3742346fb","observation_id":"654b41f6-ab10-407d-b8f7-993883d72e5f","resolution":{"observed_at":"2026-06-29T17:03:40.758725Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.18225","last_updated":"2024-02-28T10:43:54Z","snapshot_observed_at":"2026-08-10T00:56:39.053255Z","submitted_at":"2024-02-28T10:43:54Z","title":"CogBench: a large language model walks into a psychology lab","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.18225","snapshot_observed_at":"2026-08-01T05:37:39.425731Z","title":"X., & Schulz, E","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.22182","last_updated":"2026-07-24T10:49:50Z","snapshot_observed_at":"2026-08-06T08:18:56.641600Z","submitted_at":"2026-07-24T10:49:50Z","title":"From Isolated Tasks to Structured Capabilities: A Multilayer Taxonomy for Large Language Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-01T05:37:39.425731Z"},"links":{"cited_paper":"/paper/2402.18225","citing_paper":"/paper/2607.22182"},"observation_digest":"sha256:999e4e96246b317f1964bcc1e64261cecc57fe80fd44427a855573cc0212f5f8","observation_id":"aaeeeb06-3ee4-43f0-b52c-98ceb31d5ee0","resolution":{"observed_at":"2026-08-01T05:37:39.425731Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2402.18225/citation-record","integrity":"/paper/2402.18225/integrity","json":"/paper/2402.18225/citation-record.json","paper":"/paper/2402.18225"},"outbound":[],"paper":{"arxiv_id":"2402.18225","last_updated":"2024-02-28T10:43:54Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-10T00:56:39.053255Z","submitted_at":"2024-02-28T10:43:54Z","title":"CogBench: a large language model walks into a psychology lab"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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:2402.18225."}