{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:LEANAULVIDZ342ZJZO5EXJHJWX","short_pith_number":"pith:LEANAULV","canonical_record":{"source":{"id":"2406.14847","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-21T03:23:37Z","cross_cats_sorted":[],"title_canon_sha256":"6be23739827f90b3d63b36bf3fe6aefa1cf70826273c00eb7439b43b02cb1664","abstract_canon_sha256":"347c5041a350f843f68b6da4db67528e43175c150e78448a2cdfc3028aec034f"},"schema_version":"1.0"},"canonical_sha256":"5900d0517540f3be6b29cbba4ba4e9b5d7acb624654d0cdceff77a0644264a9a","source":{"kind":"arxiv","id":"2406.14847","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.14847","created_at":"2026-07-05T09:58:21Z"},{"alias_kind":"arxiv_version","alias_value":"2406.14847v2","created_at":"2026-07-05T09:58:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.14847","created_at":"2026-07-05T09:58:21Z"},{"alias_kind":"pith_short_12","alias_value":"LEANAULVIDZ3","created_at":"2026-07-05T09:58:21Z"},{"alias_kind":"pith_short_16","alias_value":"LEANAULVIDZ342ZJ","created_at":"2026-07-05T09:58:21Z"},{"alias_kind":"pith_short_8","alias_value":"LEANAULV","created_at":"2026-07-05T09:58:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:LEANAULVIDZ342ZJZO5EXJHJWX","target":"record","payload":{"canonical_record":{"source":{"id":"2406.14847","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-21T03:23:37Z","cross_cats_sorted":[],"title_canon_sha256":"6be23739827f90b3d63b36bf3fe6aefa1cf70826273c00eb7439b43b02cb1664","abstract_canon_sha256":"347c5041a350f843f68b6da4db67528e43175c150e78448a2cdfc3028aec034f"},"schema_version":"1.0"},"canonical_sha256":"5900d0517540f3be6b29cbba4ba4e9b5d7acb624654d0cdceff77a0644264a9a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:58:21.773267Z","signature_b64":"R10aQaWhR/xLmp7BaGsBn25zX87ioA3Q5KhAx5YE5N9BvtXothuPcwEYPkbOUSQa7gC88p3aZqJdgLD7lT/bCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5900d0517540f3be6b29cbba4ba4e9b5d7acb624654d0cdceff77a0644264a9a","last_reissued_at":"2026-07-05T09:58:21.772778Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:58:21.772778Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.14847","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:58:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dPRHqOIa2j4TFUbJIQpSMYBJxZ3al14rKc7hPpgk8XpTNPt86p7RHgrqahUD8AkpRvtm8lrR8m1wOdhjZCggDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T12:57:45.915729Z"},"content_sha256":"673fe9934e65869861e982f4c9502ffc29b51f2bcc45c8039d0bad59c42db86a","schema_version":"1.0","event_id":"sha256:673fe9934e65869861e982f4c9502ffc29b51f2bcc45c8039d0bad59c42db86a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:LEANAULVIDZ342ZJZO5EXJHJWX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fair Text to Medical Image Diffusion Model with Subgroup Distribution Aligned Tuning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Fangfang Fan, Georges El Fakhri, Jingzhao Rong, Qingyu Chen, Xiaofeng Liu, Xu Han, Zhen Li","submitted_at":"2024-06-21T03:23:37Z","abstract_excerpt":"The text to medical image (T2MedI) with latent diffusion model has great potential to alleviate the scarcity of medical imaging data and explore the underlying appearance distribution of lesions in a specific patient status description. However, as the text to nature image models, we show that the T2MedI model can also bias to some subgroups to overlook the minority ones in the training set. In this work, we first build a T2MedI model based on the pre-trained Imagen model, which has the fixed contrastive language-image pre-training (CLIP) text encoder, while its decoder has been fine-tuned on "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.14847","kind":"arxiv","version":2},"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/2406.14847/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":"2026-07-05T09:58:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ey1yaVw+Z5yoTK5g9VtX/l56Usog/ueQ3zY/4HA4smljYdp2PORH2gVsJ+bQeiFhkiAKFCOAL2Cb1Y9yWI7/Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T12:57:45.916243Z"},"content_sha256":"115bd87ea1257d9bf8e89567764aeab4c9cbb20e23845c36569100ed77ba6bed","schema_version":"1.0","event_id":"sha256:115bd87ea1257d9bf8e89567764aeab4c9cbb20e23845c36569100ed77ba6bed"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LEANAULVIDZ342ZJZO5EXJHJWX/bundle.json","state_url":"https://pith.science/pith/LEANAULVIDZ342ZJZO5EXJHJWX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LEANAULVIDZ342ZJZO5EXJHJWX/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":"2026-08-07T12:57:45Z","links":{"resolver":"https://pith.science/pith/LEANAULVIDZ342ZJZO5EXJHJWX","bundle":"https://pith.science/pith/LEANAULVIDZ342ZJZO5EXJHJWX/bundle.json","state":"https://pith.science/pith/LEANAULVIDZ342ZJZO5EXJHJWX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LEANAULVIDZ342ZJZO5EXJHJWX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:LEANAULVIDZ342ZJZO5EXJHJWX","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":"347c5041a350f843f68b6da4db67528e43175c150e78448a2cdfc3028aec034f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-21T03:23:37Z","title_canon_sha256":"6be23739827f90b3d63b36bf3fe6aefa1cf70826273c00eb7439b43b02cb1664"},"schema_version":"1.0","source":{"id":"2406.14847","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.14847","created_at":"2026-07-05T09:58:21Z"},{"alias_kind":"arxiv_version","alias_value":"2406.14847v2","created_at":"2026-07-05T09:58:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.14847","created_at":"2026-07-05T09:58:21Z"},{"alias_kind":"pith_short_12","alias_value":"LEANAULVIDZ3","created_at":"2026-07-05T09:58:21Z"},{"alias_kind":"pith_short_16","alias_value":"LEANAULVIDZ342ZJ","created_at":"2026-07-05T09:58:21Z"},{"alias_kind":"pith_short_8","alias_value":"LEANAULV","created_at":"2026-07-05T09:58:21Z"}],"graph_snapshots":[{"event_id":"sha256:115bd87ea1257d9bf8e89567764aeab4c9cbb20e23845c36569100ed77ba6bed","target":"graph","created_at":"2026-07-05T09:58:21Z","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/2406.14847/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The text to medical image (T2MedI) with latent diffusion model has great potential to alleviate the scarcity of medical imaging data and explore the underlying appearance distribution of lesions in a specific patient status description. However, as the text to nature image models, we show that the T2MedI model can also bias to some subgroups to overlook the minority ones in the training set. In this work, we first build a T2MedI model based on the pre-trained Imagen model, which has the fixed contrastive language-image pre-training (CLIP) text encoder, while its decoder has been fine-tuned on ","authors_text":"Fangfang Fan, Georges El Fakhri, Jingzhao Rong, Qingyu Chen, Xiaofeng Liu, Xu Han, Zhen Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-21T03:23:37Z","title":"Fair Text to Medical Image Diffusion Model with Subgroup Distribution Aligned Tuning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.14847","kind":"arxiv","version":2},"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":"sha256:673fe9934e65869861e982f4c9502ffc29b51f2bcc45c8039d0bad59c42db86a","target":"record","created_at":"2026-07-05T09:58:21Z","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":"347c5041a350f843f68b6da4db67528e43175c150e78448a2cdfc3028aec034f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-21T03:23:37Z","title_canon_sha256":"6be23739827f90b3d63b36bf3fe6aefa1cf70826273c00eb7439b43b02cb1664"},"schema_version":"1.0","source":{"id":"2406.14847","kind":"arxiv","version":2}},"canonical_sha256":"5900d0517540f3be6b29cbba4ba4e9b5d7acb624654d0cdceff77a0644264a9a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5900d0517540f3be6b29cbba4ba4e9b5d7acb624654d0cdceff77a0644264a9a","first_computed_at":"2026-07-05T09:58:21.772778Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:58:21.772778Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"R10aQaWhR/xLmp7BaGsBn25zX87ioA3Q5KhAx5YE5N9BvtXothuPcwEYPkbOUSQa7gC88p3aZqJdgLD7lT/bCw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:58:21.773267Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.14847","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:673fe9934e65869861e982f4c9502ffc29b51f2bcc45c8039d0bad59c42db86a","sha256:115bd87ea1257d9bf8e89567764aeab4c9cbb20e23845c36569100ed77ba6bed"],"state_sha256":"62d8ddb88eabe5255f655a5e8d791894103e236a90ba9275a03528ea5bd7013b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BUbsbFQQ4zjoDAJZZPYVVBaDY5ZtnEIh+7tfiNPsA8Fiby9FxLkCNxrZygy4NBOp1LRYZwO3a/Nv7rtR8D/rCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T12:57:45.920418Z","bundle_sha256":"0a0c404feb3daab0b1088f005ab254b20796cfdbfdb24a22a1fa1c4dba17f96d"}}