{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:FWLJF2SWFXKGHFPRTED6KNRIO6","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"57ec188010c906c36e7a92c9ca8fb94b668c2353d6f687529082c990633eb7ec","cross_cats_sorted":["cs.AI","cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-04T09:14:56Z","title_canon_sha256":"85e6fd82e57d7bfe3109101eb42d4dd0e4c55a5d9cfffc024fc7780be6e6d3a1"},"schema_version":"1.0","source":{"id":"2412.03148","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.03148","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"arxiv_version","alias_value":"2412.03148v1","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.03148","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"pith_short_12","alias_value":"FWLJF2SWFXKG","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"pith_short_16","alias_value":"FWLJF2SWFXKGHFPR","created_at":"2026-07-05T09:44:25Z"},{"alias_kind":"pith_short_8","alias_value":"FWLJF2SW","created_at":"2026-07-05T09:44:25Z"}],"graph_snapshots":[{"event_id":"sha256:80fcfa3edf7f5068b0f466f32b52390a24c1c3a381fb5d84cc7005fc2cd7997f","target":"graph","created_at":"2026-07-05T09:44:25Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2412.03148/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) have demonstrated impressive capabilities in role-playing tasks. However, there is limited research on whether LLMs can accurately simulate user behavior in real-world scenarios, such as social media. This requires models to effectively analyze a user's history and simulate their role. In this paper, we introduce \\textbf{FineRob}, a novel fine-grained behavior simulation dataset. We collect the complete behavioral history of 1,866 distinct users across three social media platforms. Each behavior is decomposed into three fine-grained elements: object, type, and cont","authors_text":"Chenwei Dai, Kun Li, Songlin Hu, Wei Zhou","cross_cats":["cs.AI","cs.CY"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-04T09:14:56Z","title":"Fine-Grained Behavior Simulation with Role-Playing Large Language Model on Social Media"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.03148","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:29be7055971c05a5487d0d0b80d4d57e4a59898889c10414eae5f291ffa5698d","target":"record","created_at":"2026-07-05T09:44:25Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"57ec188010c906c36e7a92c9ca8fb94b668c2353d6f687529082c990633eb7ec","cross_cats_sorted":["cs.AI","cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-04T09:14:56Z","title_canon_sha256":"85e6fd82e57d7bfe3109101eb42d4dd0e4c55a5d9cfffc024fc7780be6e6d3a1"},"schema_version":"1.0","source":{"id":"2412.03148","kind":"arxiv","version":1}},"canonical_sha256":"2d9692ea562dd46395f19907e5362877bc425b16e7c5a0239cbdad02e54cb7f8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2d9692ea562dd46395f19907e5362877bc425b16e7c5a0239cbdad02e54cb7f8","first_computed_at":"2026-07-05T09:44:25.595749Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:44:25.595749Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3ugB/qXC71Xh4W1BMJzL0OEscw1BYQAyypyBQgStESLj2Yys3DDrGQsW36CV77i6J6EJwgFFUZvATxY8GK0HCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:44:25.596252Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.03148","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:29be7055971c05a5487d0d0b80d4d57e4a59898889c10414eae5f291ffa5698d","sha256:80fcfa3edf7f5068b0f466f32b52390a24c1c3a381fb5d84cc7005fc2cd7997f"],"state_sha256":"46aeaf2bb241e0dfbbc60aa06f790352b59daf04441684f7f8b0d2a996d0a596"}