{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:A5LES7BGXEHJQKSDDAOVAVSLFX","short_pith_number":"pith:A5LES7BG","canonical_record":{"source":{"id":"2507.13541","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-07-17T21:21:54Z","cross_cats_sorted":[],"title_canon_sha256":"c2e4b1783327399432cd28c71bfd2acbbb3a38e1fad00a34c575bd9d15a91511","abstract_canon_sha256":"b4b8ad80674ce440eb10c8a14b3c2ab30b543bd3d66a11c101c7edf592edb64b"},"schema_version":"1.0"},"canonical_sha256":"0756497c26b90e982a43181d50564b2dc7b07459c05303c4790eab5891a63850","source":{"kind":"arxiv","id":"2507.13541","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"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:A5LES7BGXEHJQKSDDAOVAVSLFX","target":"record","payload":{"canonical_record":{"source":{"id":"2507.13541","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-07-17T21:21:54Z","cross_cats_sorted":[],"title_canon_sha256":"c2e4b1783327399432cd28c71bfd2acbbb3a38e1fad00a34c575bd9d15a91511","abstract_canon_sha256":"b4b8ad80674ce440eb10c8a14b3c2ab30b543bd3d66a11c101c7edf592edb64b"},"schema_version":"1.0"},"canonical_sha256":"0756497c26b90e982a43181d50564b2dc7b07459c05303c4790eab5891a63850","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:39:18.947136Z","signature_b64":"sdw313vDwq1Q7kzgxWyI5wDVOfg6Aa49SRvL2ujk4oMc9DJTTBt3Pibemfi/wmQpUMQKjioRZ9LaStDl39G1Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0756497c26b90e982a43181d50564b2dc7b07459c05303c4790eab5891a63850","last_reissued_at":"2026-07-05T11:39:18.946700Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:39:18.946700Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.13541","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:39:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6/yHGTwII+dqlG2twxQA1nPM+nv4RSFt06d9MF2RUGbV6LYATcihiZiQm9uEswhL14Vq3iRcUCYD972fr0YbCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T11:45:31.250370Z"},"content_sha256":"6137785dafe680a38b5b534d2ef07cca048a8727684678379718c1875ca53947","schema_version":"1.0","event_id":"sha256:6137785dafe680a38b5b534d2ef07cca048a8727684678379718c1875ca53947"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:A5LES7BGXEHJQKSDDAOVAVSLFX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PrefPalette: Personalized Preference Modeling with Latent Attributes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Andrew Cohen, Ansong Ni, Asli Celikyilmaz, Chan Young Park, Hunter Lang, Jacqueline He, Melanie Sclar, Puxin Xu, Shuyue Stella Li, Yulia Tsvetkov","submitted_at":"2025-07-17T21:21:54Z","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"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.13541","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/2507.13541/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:39:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cjYdFcjYOmc1Kj8QOT4eYTbN7/GOfFZ/brPt2hlQRDEctQAOPVe3C4DAuu7v+SN/xkZE+HYfFLEx2rUIiP0SBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T11:45:31.250886Z"},"content_sha256":"f3ba858eb3ddb3f46f4029aeb7904a4e898f68052e4b180deff95f9d95081507","schema_version":"1.0","event_id":"sha256:f3ba858eb3ddb3f46f4029aeb7904a4e898f68052e4b180deff95f9d95081507"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/A5LES7BGXEHJQKSDDAOVAVSLFX/bundle.json","state_url":"https://pith.science/pith/A5LES7BGXEHJQKSDDAOVAVSLFX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/A5LES7BGXEHJQKSDDAOVAVSLFX/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-06T11:45:31Z","links":{"resolver":"https://pith.science/pith/A5LES7BGXEHJQKSDDAOVAVSLFX","bundle":"https://pith.science/pith/A5LES7BGXEHJQKSDDAOVAVSLFX/bundle.json","state":"https://pith.science/pith/A5LES7BGXEHJQKSDDAOVAVSLFX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/A5LES7BGXEHJQKSDDAOVAVSLFX/bundle.json"},"state":{"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"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S90lIbQwqRaWRlz/jtHfruyks2fo7GvEB71RC0NeVnnaah20U0z911XWfv8aQjLczj++SEHGsbDwAaVfDaraDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T11:45:31.255817Z","bundle_sha256":"f7eb837a5f2d1741347f735220b6b3324261ffe9b3828f9f691ab56b83ba78d9"}}