{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:UXEQMP44UA76ZLHX35CS6BA2CS","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":"f8dced43d2cf9a033404820e0e86aa570f2d0953d1a6363894c07233476389d9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-18T16:11:54Z","title_canon_sha256":"91ffb89f932f4f0193a4516be3a39ec55e1ed79f8ca224b3f794ee2f6a5961e1"},"schema_version":"1.0","source":{"id":"2502.12988","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.12988","created_at":"2026-07-05T11:42:26Z"},{"alias_kind":"arxiv_version","alias_value":"2502.12988v3","created_at":"2026-07-05T11:42:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.12988","created_at":"2026-07-05T11:42:26Z"},{"alias_kind":"pith_short_12","alias_value":"UXEQMP44UA76","created_at":"2026-07-05T11:42:26Z"},{"alias_kind":"pith_short_16","alias_value":"UXEQMP44UA76ZLHX","created_at":"2026-07-05T11:42:26Z"},{"alias_kind":"pith_short_8","alias_value":"UXEQMP44","created_at":"2026-07-05T11:42:26Z"}],"graph_snapshots":[{"event_id":"sha256:7538de7e3492446961be9969b7df99e5a3d07e9a2d0ec8b951a4e7ef3cb45237","target":"graph","created_at":"2026-07-05T11:42:26Z","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/2502.12988/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Previous approaches to persona simulation large language models (LLMs) have typically relied on learning basic biographical information, or using limited role-play dialogue datasets to capture a character's responses. However, a holistic representation of an individual goes beyond surface-level facts or conversations to deeper thoughts and thinking. In this work, we introduce CharacterBot, a model designed to replicate both the linguistic patterns and distinctive thought patterns as manifested in the textual works of a character. Using Lu Xun, a renowned Chinese writer as a case study, we prop","authors_text":"Duzhen Zhang, Ishita Agrawal, Le Song, Shen Gao, Xiuying Chen, Zixiao Wang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-18T16:11:54Z","title":"Beyond Profile: From Surface-Level Facts to Deep Persona Simulation in LLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.12988","kind":"arxiv","version":3},"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":"sha256:5c0ea8875a0ec07a1fda00d0b50633144b6f315f1f04ca7b7553fcfbffbeef25","target":"record","created_at":"2026-07-05T11:42:26Z","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":"f8dced43d2cf9a033404820e0e86aa570f2d0953d1a6363894c07233476389d9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-18T16:11:54Z","title_canon_sha256":"91ffb89f932f4f0193a4516be3a39ec55e1ed79f8ca224b3f794ee2f6a5961e1"},"schema_version":"1.0","source":{"id":"2502.12988","kind":"arxiv","version":3}},"canonical_sha256":"a5c9063f9ca03fecacf7df452f041a14b241760174596620a30140f68df816df","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a5c9063f9ca03fecacf7df452f041a14b241760174596620a30140f68df816df","first_computed_at":"2026-07-05T11:42:26.063043Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:42:26.063043Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"t1F9m2RFUY49X8+7JyDfYu1R4CuytGDKPFSCom3ry5wqOVYKJzLNdbRZKBckpdSl36GNDsvExEhUd9EtvaNhDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:42:26.063492Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.12988","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5c0ea8875a0ec07a1fda00d0b50633144b6f315f1f04ca7b7553fcfbffbeef25","sha256:7538de7e3492446961be9969b7df99e5a3d07e9a2d0ec8b951a4e7ef3cb45237"],"state_sha256":"7142139252310ccc1577c7afd949af7320212f8afa33bcbfdccbbe0df46a370d"}