{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:TIYVVITHT5VU6U7ALWAPMPIMTA","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":"2419371f90a44775c2eecf6a327dc516cfd945aba4659900290f46f8d18ab9fb","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-03T13:09:18Z","title_canon_sha256":"8c21cfc83767c2717bdd8f1551c6c877f63c6637f4efe66542fc700c0e0aa6c5"},"schema_version":"1.0","source":{"id":"2507.02595","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.02595","created_at":"2026-07-05T11:31:31Z"},{"alias_kind":"arxiv_version","alias_value":"2507.02595v1","created_at":"2026-07-05T11:31:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.02595","created_at":"2026-07-05T11:31:31Z"},{"alias_kind":"pith_short_12","alias_value":"TIYVVITHT5VU","created_at":"2026-07-05T11:31:31Z"},{"alias_kind":"pith_short_16","alias_value":"TIYVVITHT5VU6U7A","created_at":"2026-07-05T11:31:31Z"},{"alias_kind":"pith_short_8","alias_value":"TIYVVITH","created_at":"2026-07-05T11:31:31Z"}],"graph_snapshots":[{"event_id":"sha256:db807bc502453db306ed6c86962c3ac12ee5c141ff77901116ce0fd4a8f6aa6c","target":"graph","created_at":"2026-07-05T11:31:31Z","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/2507.02595/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multiperspective Fusion (MPF) is a novel posttraining alignment framework for large language models (LLMs) developed in response to the growing need for easy bias mitigation. Built on top of the SAGED pipeline, an automated system for constructing bias benchmarks and extracting interpretable baseline distributions, MPF leverages multiperspective generations to expose and align biases in LLM outputs with nuanced, humanlike baselines. By decomposing baseline, such as sentiment distributions from HR professionals, into interpretable perspective components, MPF guides generation through sampling a","authors_text":"Adriano Koshiyama, Emre Kazim, PeiHsin Lin, Ruibo Zhang, Xin Guan, Zekun Wu, Ze Wang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-03T13:09:18Z","title":"MPF: Aligning and Debiasing Language Models post Deployment via Multi Perspective Fusion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.02595","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:bab15aff9b8aa48191f98547bf2c79be78959cffbf51bb86f5eb51a4b5cbe0cf","target":"record","created_at":"2026-07-05T11:31:31Z","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":"2419371f90a44775c2eecf6a327dc516cfd945aba4659900290f46f8d18ab9fb","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-03T13:09:18Z","title_canon_sha256":"8c21cfc83767c2717bdd8f1551c6c877f63c6637f4efe66542fc700c0e0aa6c5"},"schema_version":"1.0","source":{"id":"2507.02595","kind":"arxiv","version":1}},"canonical_sha256":"9a315aa2679f6b4f53e05d80f63d0c983fedb9f97aa19e113499010ca078ca5c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9a315aa2679f6b4f53e05d80f63d0c983fedb9f97aa19e113499010ca078ca5c","first_computed_at":"2026-07-05T11:31:31.510180Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:31:31.510180Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4fRxzD1FfCZuYvgoyBLkQ7nRNogzA3WuRp1jP/7KNs6NTjFZkuLL1vtOBL15pWvQ45TsmzoKt2Ir8b9SI79iCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:31:31.510642Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.02595","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bab15aff9b8aa48191f98547bf2c79be78959cffbf51bb86f5eb51a4b5cbe0cf","sha256:db807bc502453db306ed6c86962c3ac12ee5c141ff77901116ce0fd4a8f6aa6c"],"state_sha256":"aa60894a851496b3bed345bcbcd46b85117d92a9a77012ad3624fd47efcc2ce9"}