{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:A5LES7BGXEHJQKSDDAOVAVSLFX","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":"b4b8ad80674ce440eb10c8a14b3c2ab30b543bd3d66a11c101c7edf592edb64b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-07-17T21:21:54Z","title_canon_sha256":"c2e4b1783327399432cd28c71bfd2acbbb3a38e1fad00a34c575bd9d15a91511"},"schema_version":"1.0","source":{"id":"2507.13541","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.13541","created_at":"2026-07-05T11:39:18Z"},{"alias_kind":"arxiv_version","alias_value":"2507.13541v1","created_at":"2026-07-05T11:39:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.13541","created_at":"2026-07-05T11:39:18Z"},{"alias_kind":"pith_short_12","alias_value":"A5LES7BGXEHJ","created_at":"2026-07-05T11:39:18Z"},{"alias_kind":"pith_short_16","alias_value":"A5LES7BGXEHJQKSD","created_at":"2026-07-05T11:39:18Z"},{"alias_kind":"pith_short_8","alias_value":"A5LES7BG","created_at":"2026-07-05T11:39:18Z"}],"graph_snapshots":[{"event_id":"sha256:f3ba858eb3ddb3f46f4029aeb7904a4e898f68052e4b180deff95f9d95081507","target":"graph","created_at":"2026-07-05T11:39:18Z","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/2507.13541/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Personalizing AI systems requires understanding not just what users prefer, but the reasons that underlie those preferences - yet current preference models typically treat human judgment as a black box. We introduce PrefPalette, a framework that decomposes preferences into attribute dimensions and tailors its preference prediction to distinct social community values in a human-interpretable manner. PrefPalette operationalizes a cognitive science principle known as multi-attribute decision making in two ways: (1) a scalable counterfactual attribute synthesis step that involves generating synthe","authors_text":"Andrew Cohen, Ansong Ni, Asli Celikyilmaz, Chan Young Park, Hunter Lang, Jacqueline He, Melanie Sclar, Puxin Xu, Shuyue Stella Li, Yulia Tsvetkov","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-07-17T21:21:54Z","title":"PrefPalette: Personalized Preference Modeling with Latent Attributes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.13541","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":"sha256:6137785dafe680a38b5b534d2ef07cca048a8727684678379718c1875ca53947","target":"record","created_at":"2026-07-05T11:39:18Z","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":"b4b8ad80674ce440eb10c8a14b3c2ab30b543bd3d66a11c101c7edf592edb64b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-07-17T21:21:54Z","title_canon_sha256":"c2e4b1783327399432cd28c71bfd2acbbb3a38e1fad00a34c575bd9d15a91511"},"schema_version":"1.0","source":{"id":"2507.13541","kind":"arxiv","version":1}},"canonical_sha256":"0756497c26b90e982a43181d50564b2dc7b07459c05303c4790eab5891a63850","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0756497c26b90e982a43181d50564b2dc7b07459c05303c4790eab5891a63850","first_computed_at":"2026-07-05T11:39:18.946700Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:39:18.946700Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sdw313vDwq1Q7kzgxWyI5wDVOfg6Aa49SRvL2ujk4oMc9DJTTBt3Pibemfi/wmQpUMQKjioRZ9LaStDl39G1Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:39:18.947136Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.13541","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6137785dafe680a38b5b534d2ef07cca048a8727684678379718c1875ca53947","sha256:f3ba858eb3ddb3f46f4029aeb7904a4e898f68052e4b180deff95f9d95081507"],"state_sha256":"9dd676a8de98af5d33eca9fb9505770752e9c49524ba23f2b51d03bd1e823204"}