{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:TKJ63OYT5VGLXBX32YPZLUJ2EB","short_pith_number":"pith:TKJ63OYT","schema_version":"1.0","canonical_sha256":"9a93edbb13ed4cbb86fbd61f95d13a20630e03e21d962124e463155be06ff6d9","source":{"kind":"arxiv","id":"2509.09867","version":1},"attestation_state":"computed","paper":{"title":"LLMs as Agentic Cooperative Players in Multiplayer UNO","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Jesse Roberts, Yago Romano Matinez","submitted_at":"2025-09-11T21:42:33Z","abstract_excerpt":"LLMs promise to assist humans -- not just by answering questions, but by offering useful guidance across a wide range of tasks. But how far does that assistance go? Can a large language model based agent actually help someone accomplish their goal as an active participant? We test this question by engaging an LLM in UNO, a turn-based card game, asking it not to win but instead help another player to do so. We built a tool that allows decoder-only LLMs to participate as agents within the RLCard game environment. These models receive full game-state information and respond using simple text prom"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2509.09867","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2025-09-11T21:42:33Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"3d2ed9193ff28f0213bfc78a9107832cdfb2b0040fa9de5148b43b84eb117ea3","abstract_canon_sha256":"1e89ec75d9a09988f0e764bb7461e0a9a0b0cacdf49e031b6fad3baeca65c226"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:09:50.921231Z","signature_b64":"/I9rCD9ylEfjZ+6iTciEXp1BdKSxs6JB7hN61/ZRfNgGTSmjF3cn1etgTVRx2YTjClMpOx07szsZaCybX6b+Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9a93edbb13ed4cbb86fbd61f95d13a20630e03e21d962124e463155be06ff6d9","last_reissued_at":"2026-07-05T12:09:50.920724Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:09:50.920724Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"LLMs as Agentic Cooperative Players in Multiplayer UNO","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Jesse Roberts, Yago Romano Matinez","submitted_at":"2025-09-11T21:42:33Z","abstract_excerpt":"LLMs promise to assist humans -- not just by answering questions, but by offering useful guidance across a wide range of tasks. But how far does that assistance go? Can a large language model based agent actually help someone accomplish their goal as an active participant? We test this question by engaging an LLM in UNO, a turn-based card game, asking it not to win but instead help another player to do so. We built a tool that allows decoder-only LLMs to participate as agents within the RLCard game environment. These models receive full game-state information and respond using simple text prom"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.09867","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2509.09867/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2509.09867","created_at":"2026-07-05T12:09:50.920791+00:00"},{"alias_kind":"arxiv_version","alias_value":"2509.09867v1","created_at":"2026-07-05T12:09:50.920791+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.09867","created_at":"2026-07-05T12:09:50.920791+00:00"},{"alias_kind":"pith_short_12","alias_value":"TKJ63OYT5VGL","created_at":"2026-07-05T12:09:50.920791+00:00"},{"alias_kind":"pith_short_16","alias_value":"TKJ63OYT5VGLXBX3","created_at":"2026-07-05T12:09:50.920791+00:00"},{"alias_kind":"pith_short_8","alias_value":"TKJ63OYT","created_at":"2026-07-05T12:09:50.920791+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/TKJ63OYT5VGLXBX32YPZLUJ2EB","json":"https://pith.science/pith/TKJ63OYT5VGLXBX32YPZLUJ2EB.json","graph_json":"https://pith.science/api/pith-number/TKJ63OYT5VGLXBX32YPZLUJ2EB/graph.json","events_json":"https://pith.science/api/pith-number/TKJ63OYT5VGLXBX32YPZLUJ2EB/events.json","paper":"https://pith.science/paper/TKJ63OYT"},"agent_actions":{"view_html":"https://pith.science/pith/TKJ63OYT5VGLXBX32YPZLUJ2EB","download_json":"https://pith.science/pith/TKJ63OYT5VGLXBX32YPZLUJ2EB.json","view_paper":"https://pith.science/paper/TKJ63OYT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2509.09867&json=true","fetch_graph":"https://pith.science/api/pith-number/TKJ63OYT5VGLXBX32YPZLUJ2EB/graph.json","fetch_events":"https://pith.science/api/pith-number/TKJ63OYT5VGLXBX32YPZLUJ2EB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TKJ63OYT5VGLXBX32YPZLUJ2EB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TKJ63OYT5VGLXBX32YPZLUJ2EB/action/storage_attestation","attest_author":"https://pith.science/pith/TKJ63OYT5VGLXBX32YPZLUJ2EB/action/author_attestation","sign_citation":"https://pith.science/pith/TKJ63OYT5VGLXBX32YPZLUJ2EB/action/citation_signature","submit_replication":"https://pith.science/pith/TKJ63OYT5VGLXBX32YPZLUJ2EB/action/replication_record"}},"created_at":"2026-07-05T12:09:50.920791+00:00","updated_at":"2026-07-05T12:09:50.920791+00:00"}