{"as_of":"2026-08-09T02:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f7f5d4dd1e212f3109e41f4047eb43f32aed9eaa8edf1f3fb1c3914c9da12cd0","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":23,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":23,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":23,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:07:04.353793Z","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":"2026-07-03T15:08:33.096987Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":"2310.18940","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-07-03T15:08:33.096987Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game","venue":null,"work_id":"75326cf6-326b-4d75-b414-b80dcb50328c","year":2023},"citing_paper":{"arxiv_id":"2402.01680","last_updated":"2024-04-19T01:15:16Z","snapshot_observed_at":"2026-08-06T19:10:15.466826Z","submitted_at":"2024-01-21T23:36:14Z","title":"Large Language Model based Multi-Agents: A Survey of Progress and Challenges","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-12T06:58:54.921355Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2402.01680"},"observation_digest":"sha256:9129ebbf5637864a1e08dd4d3c9422fe5c24a1b75192a45073ba68388779e9f2","observation_id":"490df0f0-82df-4af1-a69c-ba60cfebe1c9","resolution":{"observed_at":"2026-05-12T06:58:56.488203Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":"2310.18940","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-07-03T15:08:33.096987Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game","venue":null,"work_id":"75326cf6-326b-4d75-b414-b80dcb50328c","year":2023},"citing_paper":{"arxiv_id":"2504.02181","last_updated":"2026-04-22T01:49:17Z","snapshot_observed_at":"2026-07-30T09:24:14.725185Z","submitted_at":"2025-04-02T23:51:27Z","title":"A Survey of Scaling in Large Language Model Reasoning","version":2},"reference_index":237,"source":"pdf_text","source_observed_at":"2026-05-22T21:20:07.238992Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2504.02181"},"observation_digest":"sha256:e0ebfe5c515b2dc52926bf44fae304cd9ec033e1e90646aefbc7d31336e09ffe","observation_id":"dd837411-6845-42ce-b050-5e709b4ca9ac","resolution":{"observed_at":"2026-05-22T21:22:09.334096Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-08-07T15:07:04.353793Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game.arXiv preprint arXiv:2310.18940, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16401","last_updated":"2025-06-12T15:02:59Z","snapshot_observed_at":"2026-08-07T14:59:29.508178Z","submitted_at":"2025-05-22T08:52:21Z","title":"Divide-Fuse-Conquer: Eliciting \"Aha Moments\" in Multi-Scenario Games","version":4},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T15:07:04.353793Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2505.16401"},"observation_digest":"sha256:cd54f0d0e0ad6f6520c278eedc08482fb939aabc24a0457dc48eb1f8a76c43e3","observation_id":"2ef590d1-f1b4-4ddb-ae4e-9ceadd28e506","resolution":{"observed_at":"2026-08-07T15:07:04.353793Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-08-07T14:47:39.661634Z","title":"Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Tom Griffiths, Yuan Cao, and Karthik Narasimhan","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.18218","last_updated":"2025-05-23T08:23:54Z","snapshot_observed_at":"2026-08-08T00:28:54.794720Z","submitted_at":"2025-05-23T08:23:54Z","title":"CoMet: Metaphor-Driven Covert Communication for Multi-Agent Language Games","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T14:47:39.661634Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2505.18218"},"observation_digest":"sha256:c8e95ea3f0f010633c1a97fdf9705cd1bbb7678978dd5b739d88f58c23159eb3","observation_id":"b0515a98-614b-43c2-b3fa-afeb71a152ea","resolution":{"observed_at":"2026-08-07T14:47:39.661634Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-08-07T13:45:26.664665Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.21588","last_updated":"2025-05-27T12:12:56Z","snapshot_observed_at":"2026-08-08T08:32:12.026914Z","submitted_at":"2025-05-27T12:12:56Z","title":"Herd Behavior: Investigating Peer Influence in LLM-based Multi-Agent Systems","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T13:45:26.664665Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2505.21588"},"observation_digest":"sha256:ac1ebd16f8d2bf700b9f2b86bc589152a1a27642d2edf9021e39224f0a583287","observation_id":"58cfe9a8-e70b-4371-83ae-b4a0db0d4051","resolution":{"observed_at":"2026-08-07T13:45:26.664665Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-08-07T12:12:49.193772Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.00160","last_updated":"2025-08-10T18:49:55Z","snapshot_observed_at":"2026-08-08T06:40:33.097815Z","submitted_at":"2025-05-30T18:58:57Z","title":"Verbal Werewolf: Engage Users with Verbalized Agentic Werewolf Game Framework","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T12:12:49.193772Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2506.00160"},"observation_digest":"sha256:edd0a1edfd6a4b3ade77a89d0f5b8e8ab9a1daf129a44bbc415f33cb8dd578d2","observation_id":"cf3576c9-61ca-4015-8fbe-f8eeb6f6097e","resolution":{"observed_at":"2026-08-07T12:12:49.193772Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":"2310.18940","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-07-03T15:08:33.096987Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game","venue":null,"work_id":"75326cf6-326b-4d75-b414-b80dcb50328c","year":2023},"citing_paper":{"arxiv_id":"2506.02546","last_updated":"2026-04-14T05:32:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-03T07:32:57Z","title":"To trust or not to trust: Attention-based Trust Management for LLM Multi-Agent Systems","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-19T11:30:47.877793Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2506.02546"},"observation_digest":"sha256:f0c332406659f8ade1f899085e621daf11c93004f89a1f85959859aec28bd55d","observation_id":"48e9303f-c0c7-439c-9a37-27e3179db960","resolution":{"observed_at":"2026-05-19T11:32:17.314349Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-08-07T11:23:20.354372Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.02683","last_updated":"2025-06-03T09:33:13Z","snapshot_observed_at":"2026-08-08T07:52:55.138772Z","submitted_at":"2025-06-03T09:33:13Z","title":"Decompose, Plan in Parallel, and Merge: A Novel Paradigm for Large Language Models based Planning with Multiple Constraints","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T11:23:20.354372Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2506.02683"},"observation_digest":"sha256:ec91be70b31cde6e26a466759873fcc716914f64a0e6e5c8dbcc50c879866a8b","observation_id":"130fce05-3acb-42d9-bc5e-ef40a59e6b25","resolution":{"observed_at":"2026-08-07T11:23:20.354372Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-08-07T04:53:23.433118Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game.arXiv preprint arXiv:2310.18940,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.09655","last_updated":"2025-06-23T07:49:08Z","snapshot_observed_at":"2026-08-08T06:12:51.430162Z","submitted_at":"2025-06-11T12:25:32Z","title":"DipLLM: Fine-Tuning LLM for Strategic Decision-making in Diplomacy","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T04:53:23.433118Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2506.09655"},"observation_digest":"sha256:c6953d3c5d5320ff748e85acb7a82ce16190a55755c5b267a1f00af8ff6326bf","observation_id":"02e2ceb1-1e8b-44b7-866d-4749bbd11b4b","resolution":{"observed_at":"2026-08-07T04:53:23.433118Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-08-06T23:50:42.421606Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game, February 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.17333","last_updated":"2025-06-19T05:54:08Z","snapshot_observed_at":"2026-08-06T23:42:12.265828Z","submitted_at":"2025-06-19T05:54:08Z","title":"AutomataGPT: Forecasting and Ruleset Inference for Two-Dimensional Cellular Automata","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T23:50:42.421606Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2506.17333"},"observation_digest":"sha256:f022b6f5438353cad8127935e1dc6340ffd10314dae9dc20fe3760a4ee776c12","observation_id":"2c0ef601-be47-4e85-b76e-2ccba2ac4f03","resolution":{"observed_at":"2026-08-06T23:50:42.421606Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-08-06T21:58:23.382577Z","title":"(F) Cannot Identify","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.22957","last_updated":"2025-08-27T20:38:04Z","snapshot_observed_at":"2026-08-08T00:28:19.441824Z","submitted_at":"2025-06-28T17:22:59Z","title":"Agent-to-Agent Theory of Mind: Testing Interlocutor Awareness among Large Language Models","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-06T21:58:23.382577Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2506.22957"},"observation_digest":"sha256:b582e2cb490886fa17861a9f61b8347b4d1d337b8af3dacb01b6ca94d3ddf17e","observation_id":"eb930169-9174-4e9a-a471-bc62190de243","resolution":{"observed_at":"2026-08-06T21:58:23.382577Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-08-06T16:42:43.303125Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.12732","last_updated":"2025-07-17T02:27:45Z","snapshot_observed_at":"2026-08-08T06:01:37.844265Z","submitted_at":"2025-07-17T02:27:45Z","title":"Strategy Adaptation in Large Language Model Werewolf Agents","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T16:42:43.303125Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2507.12732"},"observation_digest":"sha256:69eb8a3b51a87d8ae996931899dd06e202b8835cc892f39545e2b07963234625","observation_id":"92d322c1-c39d-43bd-a62f-6b4f60d6ff18","resolution":{"observed_at":"2026-08-06T16:42:43.303125Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-08-06T15:29:48.057561Z","title":"Language agents with reinforcement learning for strate- gic play in the werewolf game","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.15761","last_updated":"2025-07-21T16:17:25Z","snapshot_observed_at":"2026-08-08T23:45:46.760379Z","submitted_at":"2025-07-21T16:17:25Z","title":"GasAgent: A Multi-Agent Framework for Automated Gas Optimization in Smart Contracts","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T15:29:48.057561Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2507.15761"},"observation_digest":"sha256:3cf26ea6f3163d4f17b5384d9f7d52d2fdb1822e56c23fe6543d4373f9ecf2e5","observation_id":"cb085b7a-1c6d-4545-a121-be71d2e0e540","resolution":{"observed_at":"2026-08-06T15:29:48.057561Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":"2310.18940","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-07-03T15:08:33.096987Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game","venue":null,"work_id":"75326cf6-326b-4d75-b414-b80dcb50328c","year":2023},"citing_paper":{"arxiv_id":"2509.23023","last_updated":"2026-05-14T13:52:45Z","snapshot_observed_at":"2026-08-03T02:05:46.573077Z","submitted_at":"2025-09-27T00:40:19Z","title":"Deceive, Detect, and Disclose: Large Language Models Play Mini-Mafia","version":3},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-05-18T13:25:17.313704Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2509.23023"},"observation_digest":"sha256:c652913c8adff4dbfe492305a1577a4c4754782b84c751b738f71a27d5893bae","observation_id":"8badb5cb-a46e-4028-b6ef-a3f66bd19f36","resolution":{"observed_at":"2026-05-18T13:26:24.830016Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":"2310.18940","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-07-03T15:08:33.096987Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game","venue":null,"work_id":"75326cf6-326b-4d75-b414-b80dcb50328c","year":2023},"citing_paper":{"arxiv_id":"2605.07301","last_updated":"2026-05-08T06:11:42Z","snapshot_observed_at":"2026-07-06T23:19:41.053744Z","submitted_at":"2026-05-08T06:11:42Z","title":"SOM: Structured Opponent Modeling for LLM-based Agents via Structural Causal Model","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-11T01:19:42.892343Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2605.07301"},"observation_digest":"sha256:e90b61e759b007388a4f56b959a5e1ae3ffd622f4c16079ac322119bcad2ca7d","observation_id":"fe3a74e8-7f7c-437e-b6b4-e3c87a5ffd12","resolution":{"observed_at":"2026-05-11T04:30:55.872771Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":"2310.18940","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-07-03T15:08:33.096987Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game","venue":null,"work_id":"75326cf6-326b-4d75-b414-b80dcb50328c","year":2023},"citing_paper":{"arxiv_id":"2605.27068","last_updated":"2026-05-26T14:19:08Z","snapshot_observed_at":"2026-08-08T00:27:41.307742Z","submitted_at":"2026-05-26T14:19:08Z","title":"QUACK: Questioning, Understanding, and Auditing Communicated Knowledge in Multimodal Social Deduction Agents","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-29T17:59:51.871639Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2605.27068"},"observation_digest":"sha256:fddd4aa301f5e5976ecb280dba04b1078b71c516959bdce82bce994dafdb861a","observation_id":"db23f596-c03c-4452-8f24-a03414a90ac5","resolution":{"observed_at":"2026-06-29T18:03:47.990753Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":"2310.18940","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-07-03T15:08:33.096987Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game","venue":null,"work_id":"75326cf6-326b-4d75-b414-b80dcb50328c","year":2023},"citing_paper":{"arxiv_id":"2605.29512","last_updated":"2026-05-28T07:33:47Z","snapshot_observed_at":"2026-07-06T23:38:56.014434Z","submitted_at":"2026-05-28T07:33:47Z","title":"MINDGAMES: A Live Arena for Evaluating Social and Strategic Reasoning in Multi-Agent LLMs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-29T07:15:27.939886Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2605.29512"},"observation_digest":"sha256:8e38ffe8297d291deb63ea77c1698229737795146855342de231d8243a76dfd7","observation_id":"e1d2defc-3b7b-4ab8-88a3-d6a698ea3672","resolution":{"observed_at":"2026-06-29T07:23:13.205074Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":"2310.18940","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-07-03T15:08:33.096987Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game","venue":null,"work_id":"75326cf6-326b-4d75-b414-b80dcb50328c","year":2023},"citing_paper":{"arxiv_id":"2606.02754","last_updated":"2026-06-01T18:20:27Z","snapshot_observed_at":"2026-08-08T20:18:11.455837Z","submitted_at":"2026-06-01T18:20:27Z","title":"$\\Psi$-Bench: Evaluating Persona-Sensitive Influencing in Persuasive Dialogues","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-28T15:11:50.051343Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2606.02754"},"observation_digest":"sha256:bc33a82667373b13b069b5846846d284fa311860998c4d8c4e80c4a4e6a400b8","observation_id":"fc218c6f-8bdd-4d52-ad8a-a21283c2250d","resolution":{"observed_at":"2026-07-01T22:36:17.654445Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":"2310.18940","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-07-03T15:08:33.096987Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game","venue":null,"work_id":"75326cf6-326b-4d75-b414-b80dcb50328c","year":2023},"citing_paper":{"arxiv_id":"2606.13608","last_updated":"2026-06-11T17:23:54Z","snapshot_observed_at":"2026-08-07T11:12:52.411120Z","submitted_at":"2026-06-11T17:23:54Z","title":"AgentBeats: Agentifying Agent Assessment for Openness, Standardization, and Reproducibility","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-06-27T06:41:41.799596Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2606.13608"},"observation_digest":"sha256:57907f0f192f2f874e9aff0ee8113f25e6c1f8071283125c0e164a06af0830ef","observation_id":"792e599e-582c-44d7-89be-708994e931a2","resolution":{"observed_at":"2026-07-03T15:08:33.098389Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":"2310.18940","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-07-03T15:08:33.096987Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game","venue":null,"work_id":"75326cf6-326b-4d75-b414-b80dcb50328c","year":2023},"citing_paper":{"arxiv_id":"2606.27397","last_updated":"2026-06-24T10:35:31Z","snapshot_observed_at":"2026-08-07T13:04:37.321863Z","submitted_at":"2026-06-24T10:35:31Z","title":"SidConArena: An Environment Evaluating Agents in Open-Ended,Positive-Sum Bargaining Game","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-06-29T01:56:22.856352Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2606.27397"},"observation_digest":"sha256:9f579e471dac53fc97ba9f93354b2486f810ab7e425b26f8a384835fe4a533d9","observation_id":"2aa167e5-9a3b-4187-ad2e-3117182ebf6a","resolution":{"observed_at":"2026-07-01T18:35:58.051667Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-07-12T00:37:46.305819Z","title":"Language agents with reinforcement learning for strategic play in the werewolf game.arXiv preprint arXiv:2310.18940, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.03695","last_updated":"2026-07-04T03:59:08Z","snapshot_observed_at":"2026-08-08T07:40:54.043481Z","submitted_at":"2026-07-04T03:59:08Z","title":"Social Networks of LLM Agents","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-07-12T00:37:46.305819Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2607.03695"},"observation_digest":"sha256:d46d905b59d24026e207cacd48a528b012ca0e5ff4ec0253f85f285c37d747e0","observation_id":"16287072-f2e2-4079-9f09-c98faeee3c8d","resolution":{"observed_at":"2026-07-12T00:37:46.305819Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-07-14T09:04:16.361753Z","title":"arXiv:2310.18940","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10814","last_updated":"2026-07-12T16:03:30Z","snapshot_observed_at":"2026-08-08T11:06:10.929529Z","submitted_at":"2026-07-12T16:03:30Z","title":"Auditing Belief-Conditioned LLM Agents in Hidden-Information Social Deduction Games","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-14T09:04:16.361753Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2607.10814"},"observation_digest":"sha256:d989bdbf657af0b59f9d8bd7d6b8c2355a3c88089a7ed9636bcecce90bf6266a","observation_id":"65914633-c973-473f-b02f-8f231c4dbd45","resolution":{"observed_at":"2026-07-14T09:04:16.361753Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18940","snapshot_observed_at":"2026-07-31T23:52:06.829105Z","title":"arXiv preprint arXiv:2310.18940 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.23333","last_updated":"2026-07-25T19:11:15Z","snapshot_observed_at":"2026-08-03T00:37:21.399146Z","submitted_at":"2026-07-25T19:11:15Z","title":"Training with (Swap) Regret Loss in a Single-Layer Self-Attention Model: A Case Study on the Probability Simplex","version":1},"reference_index":200,"source":"arxiv_source","source_observed_at":"2026-07-31T23:52:06.829105Z"},"links":{"cited_paper":"/paper/2310.18940","citing_paper":"/paper/2607.23333"},"observation_digest":"sha256:ab947f1710f1cc1384ec5e3c396494a1597323a64be004b6894fea9fcbffdd2f","observation_id":"804842a6-2ce5-4f58-a402-88ac72c9f0b0","resolution":{"observed_at":"2026-07-31T23:52:06.829105Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2310.18940/citation-record","integrity":"/paper/2310.18940/integrity","json":"/paper/2310.18940/citation-record.json","paper":"/paper/2310.18940"},"outbound":[],"paper":{"arxiv_id":"2310.18940","last_updated":"2025-05-29T08:46:38Z","latest_version":4,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-08T00:26:58.865814Z","submitted_at":"2023-10-29T09:02:57Z","title":"Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game"},"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 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:2310.18940."}