{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:KKN63JWDBCWTDBCZMOC7CALDNH","short_pith_number":"pith:KKN63JWD","canonical_record":{"source":{"id":"2507.13383","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-15T21:02:35Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"734ca407efe6d081f7d69007d1f93c22d6b175f5d9987a74f1498ea9f7e800a8","abstract_canon_sha256":"645b087d6bfcb94d74e0ec6f66224cb18cdd89e86f9dd0fb010295e2d982a3f3"},"schema_version":"1.0"},"canonical_sha256":"529beda6c308ad3184596385f1016369f0e36a4d4479cf83d318c70f5f27f3f6","source":{"kind":"arxiv","id":"2507.13383","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.13383","created_at":"2026-07-05T11:39:16Z"},{"alias_kind":"arxiv_version","alias_value":"2507.13383v1","created_at":"2026-07-05T11:39:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.13383","created_at":"2026-07-05T11:39:16Z"},{"alias_kind":"pith_short_12","alias_value":"KKN63JWDBCWT","created_at":"2026-07-05T11:39:16Z"},{"alias_kind":"pith_short_16","alias_value":"KKN63JWDBCWTDBCZ","created_at":"2026-07-05T11:39:16Z"},{"alias_kind":"pith_short_8","alias_value":"KKN63JWD","created_at":"2026-07-05T11:39:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:KKN63JWDBCWTDBCZMOC7CALDNH","target":"record","payload":{"canonical_record":{"source":{"id":"2507.13383","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-15T21:02:35Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"734ca407efe6d081f7d69007d1f93c22d6b175f5d9987a74f1498ea9f7e800a8","abstract_canon_sha256":"645b087d6bfcb94d74e0ec6f66224cb18cdd89e86f9dd0fb010295e2d982a3f3"},"schema_version":"1.0"},"canonical_sha256":"529beda6c308ad3184596385f1016369f0e36a4d4479cf83d318c70f5f27f3f6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:39:16.363837Z","signature_b64":"5UUvpjA92xpxQVhvYyLgHSwyf7dABHUM4ylh5S4DjdDwcp0Ap4FrLwQ3cLgFzueLHIeimegc94V3XyBE/O+ZBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"529beda6c308ad3184596385f1016369f0e36a4d4479cf83d318c70f5f27f3f6","last_reissued_at":"2026-07-05T11:39:16.363353Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:39:16.363353Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.13383","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":"2026-07-05T11:39:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MeerQ+9R6bCoJjUGySXU7LJ11JHQNTgifrpLm4Gpx8zZEajgKWiLSOiO3F8FqRPUkcWRJt9Hw5CeZTZHUsWNCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T10:40:04.146956Z"},"content_sha256":"bb37010596b61fa38d6236ff4b579ac65faa7e6f004543cbe7dcf12d9cf35912","schema_version":"1.0","event_id":"sha256:bb37010596b61fa38d6236ff4b579ac65faa7e6f004543cbe7dcf12d9cf35912"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:KKN63JWDBCWTDBCZMOC7CALDNH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Whose View of Safety? A Deep DIVE Dataset for Pluralistic Alignment of Text-to-Image Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Aida Mostafazadeh Davani, Alicia Parrish, Charvi Rastogi, Ding Wang, Lora Aroyo, Mark D\\'iaz, Michela Paganini, Pushkar Mishra, Roma Patel, Tian Huey Teh, Verena Rieser, Vinodkumar Prabhakaran, Zoe Ashwood","submitted_at":"2025-07-15T21:02:35Z","abstract_excerpt":"Current text-to-image (T2I) models often fail to account for diverse human experiences, leading to misaligned systems. We advocate for pluralistic alignment, where an AI understands and is steerable towards diverse, and often conflicting, human values. Our work provides three core contributions to achieve this in T2I models. First, we introduce a novel dataset for Diverse Intersectional Visual Evaluation (DIVE) -- the first multimodal dataset for pluralistic alignment. It enable deep alignment to diverse safety perspectives through a large pool of demographically intersectional human raters wh"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.13383","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/2507.13383/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":"2026-07-05T11:39:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FuIFVbjCRFy+gTOf7xVBQmZWAHsVqu1F4h6XPsBSqr9qjzBKywfJc9CCcMIru1eWl0JBLxTqdF3MHHYn5ebaCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T10:40:04.147497Z"},"content_sha256":"26d8e8499dd976a31865a0223a481670a2e6f0e19788689f44dcc78dedcdd7e6","schema_version":"1.0","event_id":"sha256:26d8e8499dd976a31865a0223a481670a2e6f0e19788689f44dcc78dedcdd7e6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KKN63JWDBCWTDBCZMOC7CALDNH/bundle.json","state_url":"https://pith.science/pith/KKN63JWDBCWTDBCZMOC7CALDNH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KKN63JWDBCWTDBCZMOC7CALDNH/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":"2026-08-04T10:40:04Z","links":{"resolver":"https://pith.science/pith/KKN63JWDBCWTDBCZMOC7CALDNH","bundle":"https://pith.science/pith/KKN63JWDBCWTDBCZMOC7CALDNH/bundle.json","state":"https://pith.science/pith/KKN63JWDBCWTDBCZMOC7CALDNH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KKN63JWDBCWTDBCZMOC7CALDNH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:KKN63JWDBCWTDBCZMOC7CALDNH","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":"645b087d6bfcb94d74e0ec6f66224cb18cdd89e86f9dd0fb010295e2d982a3f3","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-15T21:02:35Z","title_canon_sha256":"734ca407efe6d081f7d69007d1f93c22d6b175f5d9987a74f1498ea9f7e800a8"},"schema_version":"1.0","source":{"id":"2507.13383","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.13383","created_at":"2026-07-05T11:39:16Z"},{"alias_kind":"arxiv_version","alias_value":"2507.13383v1","created_at":"2026-07-05T11:39:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.13383","created_at":"2026-07-05T11:39:16Z"},{"alias_kind":"pith_short_12","alias_value":"KKN63JWDBCWT","created_at":"2026-07-05T11:39:16Z"},{"alias_kind":"pith_short_16","alias_value":"KKN63JWDBCWTDBCZ","created_at":"2026-07-05T11:39:16Z"},{"alias_kind":"pith_short_8","alias_value":"KKN63JWD","created_at":"2026-07-05T11:39:16Z"}],"graph_snapshots":[{"event_id":"sha256:26d8e8499dd976a31865a0223a481670a2e6f0e19788689f44dcc78dedcdd7e6","target":"graph","created_at":"2026-07-05T11:39:16Z","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/2507.13383/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Current text-to-image (T2I) models often fail to account for diverse human experiences, leading to misaligned systems. We advocate for pluralistic alignment, where an AI understands and is steerable towards diverse, and often conflicting, human values. Our work provides three core contributions to achieve this in T2I models. First, we introduce a novel dataset for Diverse Intersectional Visual Evaluation (DIVE) -- the first multimodal dataset for pluralistic alignment. It enable deep alignment to diverse safety perspectives through a large pool of demographically intersectional human raters wh","authors_text":"Aida Mostafazadeh Davani, Alicia Parrish, Charvi Rastogi, Ding Wang, Lora Aroyo, Mark D\\'iaz, Michela Paganini, Pushkar Mishra, Roma Patel, Tian Huey Teh, Verena Rieser, Vinodkumar Prabhakaran, Zoe Ashwood","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-15T21:02:35Z","title":"Whose View of Safety? A Deep DIVE Dataset for Pluralistic Alignment of Text-to-Image Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.13383","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:bb37010596b61fa38d6236ff4b579ac65faa7e6f004543cbe7dcf12d9cf35912","target":"record","created_at":"2026-07-05T11:39:16Z","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":"645b087d6bfcb94d74e0ec6f66224cb18cdd89e86f9dd0fb010295e2d982a3f3","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-15T21:02:35Z","title_canon_sha256":"734ca407efe6d081f7d69007d1f93c22d6b175f5d9987a74f1498ea9f7e800a8"},"schema_version":"1.0","source":{"id":"2507.13383","kind":"arxiv","version":1}},"canonical_sha256":"529beda6c308ad3184596385f1016369f0e36a4d4479cf83d318c70f5f27f3f6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"529beda6c308ad3184596385f1016369f0e36a4d4479cf83d318c70f5f27f3f6","first_computed_at":"2026-07-05T11:39:16.363353Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:39:16.363353Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5UUvpjA92xpxQVhvYyLgHSwyf7dABHUM4ylh5S4DjdDwcp0Ap4FrLwQ3cLgFzueLHIeimegc94V3XyBE/O+ZBA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:39:16.363837Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.13383","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bb37010596b61fa38d6236ff4b579ac65faa7e6f004543cbe7dcf12d9cf35912","sha256:26d8e8499dd976a31865a0223a481670a2e6f0e19788689f44dcc78dedcdd7e6"],"state_sha256":"c10dceef399365d620c0f428b732dd9af5f4592bb674dfc0aae29357b2b2178f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Cx0oCkvdNSxZUWUFD5jUDGVPpT5SLcxUAdIpXTNnh2nfJk/5XKnmlQ4/VaTbKZ3rucnm3Y774uwIIOZ0wKzZBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T10:40:04.155877Z","bundle_sha256":"ee73fc671c7ba7d83aa888138896e38bead2e9c011096d6d9658bdf702ebdb27"}}