{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:WCW25JIH4ZRPII7TLXQSM2LUDP","short_pith_number":"pith:WCW25JIH","schema_version":"1.0","canonical_sha256":"b0adaea507e662f423f35de12669741bd90710466611c2641e06367af35a23c1","source":{"kind":"arxiv","id":"2607.26393","version":1},"attestation_state":"computed","paper":{"title":"CaM-Wolf: Causal-Aware Multimodal Agents for Social Deduction Games","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Deheng Ye, Hao Wang, Jiarui He, Nanjie Yao, Peilin Zhao, Zheng Zhang","submitted_at":"2026-07-29T01:58:36Z","abstract_excerpt":"Social deduction games (SDGs) such as Werewolf have become challenging testbeds for AI agents. These games require complex social skills such as reasoning, deception, and collaboration. While recent advances in large language models (LLMs) have driven significant progress in SDG agents, current approaches are predominantly text-based, overlooking the multimodal nature that is fundamental to human social interaction. To bridge this gap, we introduce CaM-Wolf, the first SDG agent that integrates multimodal perception and generation. CaM-Wolf processes video inputs from other players, employs a c"},"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":"2607.26393","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-07-29T01:58:36Z","cross_cats_sorted":[],"title_canon_sha256":"dabd84c73a4c8d246744e4db40b746abc898a29ff2209faa964b5c3414e46c1a","abstract_canon_sha256":"ecdece28ec432aee2cf9a3b4b75b08482a0ced0bb58623ba33fce6d12b18cdd5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b0adaea507e662f423f35de12669741bd90710466611c2641e06367af35a23c1","last_reissued_at":"2026-07-30T01:18:17.893089Z","signature_status":"unsigned_v0","first_computed_at":"2026-07-30T01:18:17.893089Z"},"graph_snapshot":{"paper":{"title":"CaM-Wolf: Causal-Aware Multimodal Agents for Social Deduction Games","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Deheng Ye, Hao Wang, Jiarui He, Nanjie Yao, Peilin Zhao, Zheng Zhang","submitted_at":"2026-07-29T01:58:36Z","abstract_excerpt":"Social deduction games (SDGs) such as Werewolf have become challenging testbeds for AI agents. These games require complex social skills such as reasoning, deception, and collaboration. While recent advances in large language models (LLMs) have driven significant progress in SDG agents, current approaches are predominantly text-based, overlooking the multimodal nature that is fundamental to human social interaction. To bridge this gap, we introduce CaM-Wolf, the first SDG agent that integrates multimodal perception and generation. CaM-Wolf processes video inputs from other players, employs a c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.26393","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/2607.26393/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":"2607.26393","created_at":"2026-07-30T01:18:17.898268+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.26393v1","created_at":"2026-07-30T01:18:17.898268+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.26393","created_at":"2026-07-30T01:18:17.898268+00:00"},{"alias_kind":"pith_short_12","alias_value":"WCW25JIH4ZRP","created_at":"2026-07-30T01:18:17.898268+00:00"},{"alias_kind":"pith_short_16","alias_value":"WCW25JIH4ZRPII7T","created_at":"2026-07-30T01:18:17.898268+00:00"},{"alias_kind":"pith_short_8","alias_value":"WCW25JIH","created_at":"2026-07-30T01:18:17.898268+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/WCW25JIH4ZRPII7TLXQSM2LUDP","json":"https://pith.science/pith/WCW25JIH4ZRPII7TLXQSM2LUDP.json","graph_json":"https://pith.science/api/pith-number/WCW25JIH4ZRPII7TLXQSM2LUDP/graph.json","events_json":"https://pith.science/api/pith-number/WCW25JIH4ZRPII7TLXQSM2LUDP/events.json","paper":"https://pith.science/paper/WCW25JIH"},"agent_actions":{"view_html":"https://pith.science/pith/WCW25JIH4ZRPII7TLXQSM2LUDP","download_json":"https://pith.science/pith/WCW25JIH4ZRPII7TLXQSM2LUDP.json","view_paper":"https://pith.science/paper/WCW25JIH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.26393&json=true","fetch_graph":"https://pith.science/api/pith-number/WCW25JIH4ZRPII7TLXQSM2LUDP/graph.json","fetch_events":"https://pith.science/api/pith-number/WCW25JIH4ZRPII7TLXQSM2LUDP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WCW25JIH4ZRPII7TLXQSM2LUDP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WCW25JIH4ZRPII7TLXQSM2LUDP/action/storage_attestation","attest_author":"https://pith.science/pith/WCW25JIH4ZRPII7TLXQSM2LUDP/action/author_attestation","sign_citation":"https://pith.science/pith/WCW25JIH4ZRPII7TLXQSM2LUDP/action/citation_signature","submit_replication":"https://pith.science/pith/WCW25JIH4ZRPII7TLXQSM2LUDP/action/replication_record"}},"created_at":"2026-07-30T01:18:17.898268+00:00","updated_at":"2026-07-30T01:18:17.898268+00:00"}