{"as_of":"2026-08-08T22:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:097619a9291c883d619e8d38c1a8d8ef8083949e814b89fbd3b15589e1e585a4","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:55:43.601392Z","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":"2026-07-02T20:57:23.624827Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.11422","last_updated":"2024-05-19T01:43:52Z","snapshot_observed_at":"2026-08-03T00:40:29.172383Z","submitted_at":"2024-05-19T01:43:52Z","title":"Large Language Models are Biased Reinforcement Learners","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.11422","snapshot_observed_at":"2026-08-07T04:55:43.601392Z","title":"Hayes, Nicolas Yax, and Stefano Palminteri","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09390","last_updated":"2025-06-11T04:43:54Z","snapshot_observed_at":"2026-08-08T19:02:49.847202Z","submitted_at":"2025-06-11T04:43:54Z","title":"Beyond Nash Equilibrium: Bounded Rationality of LLMs and humans in Strategic Decision-making","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T04:55:43.601392Z"},"links":{"cited_paper":"/paper/2405.11422","citing_paper":"/paper/2506.09390"},"observation_digest":"sha256:1efb9a598a11c53dc5190507830ca269af329f676a2ff3b6399a66a6115067bd","observation_id":"5659372e-2c6b-4997-990c-864df622c91e","resolution":{"observed_at":"2026-08-07T04:55:43.601392Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.11422","last_updated":"2024-05-19T01:43:52Z","snapshot_observed_at":"2026-08-03T00:40:29.172383Z","submitted_at":"2024-05-19T01:43:52Z","title":"Large Language Models are Biased Reinforcement Learners","version":1},"cited_work":{"arxiv_id":"2405.11422","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.11422","snapshot_observed_at":"2026-07-02T20:57:23.624827Z","title":"Large language models are biased reinforcement learners.arXiv preprint arXiv:2405.11422, 2024","venue":null,"work_id":"ebcbe2e2-05c2-45e6-9ca7-c4ceec4d1306","year":2024},"citing_paper":{"arxiv_id":"2606.07988","last_updated":"2026-06-06T05:35:31Z","snapshot_observed_at":"2026-07-06T23:47:33.680573Z","submitted_at":"2026-06-06T05:35:31Z","title":"PAFO: Pareto Fairness Optimization for Personalized Reward Modeling","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-27T20:00:05.900814Z"},"links":{"cited_paper":"/paper/2405.11422","citing_paper":"/paper/2606.07988"},"observation_digest":"sha256:0870cf7540769455cdc53bd6b2e18d293bd2331d33e5a249b65ad0465e1e89c7","observation_id":"57b0239b-03b2-4b29-998f-a88b45122f48","resolution":{"observed_at":"2026-07-02T20:57:23.626286Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2405.11422/citation-record","integrity":"/paper/2405.11422/integrity","json":"/paper/2405.11422/citation-record.json","paper":"/paper/2405.11422"},"outbound":[],"paper":{"arxiv_id":"2405.11422","last_updated":"2024-05-19T01:43:52Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-03T00:40:29.172383Z","submitted_at":"2024-05-19T01:43:52Z","title":"Large Language Models are Biased Reinforcement Learners"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.11422."}