{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:EIE2VBL3DCMWX3KKNDLGW22VMG","short_pith_number":"pith:EIE2VBL3","canonical_record":{"source":{"id":"2410.15618","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-21T03:40:29Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"4160ba5839a94a5d80c9e2a58041294e1671d6b8852ce05d4d33a2f57384501d","abstract_canon_sha256":"743877f2cb06022bb65235201a98b832d66cebdcd573bea5fc8cea12b24c5bac"},"schema_version":"1.0"},"canonical_sha256":"2209aa857b18996bed4a68d66b6b556180c4dc60fe296ae13e50dbfe491e0f51","source":{"kind":"arxiv","id":"2410.15618","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.15618","created_at":"2026-07-05T11:08:01Z"},{"alias_kind":"arxiv_version","alias_value":"2410.15618v4","created_at":"2026-07-05T11:08:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.15618","created_at":"2026-07-05T11:08:01Z"},{"alias_kind":"pith_short_12","alias_value":"EIE2VBL3DCMW","created_at":"2026-07-05T11:08:01Z"},{"alias_kind":"pith_short_16","alias_value":"EIE2VBL3DCMWX3KK","created_at":"2026-07-05T11:08:01Z"},{"alias_kind":"pith_short_8","alias_value":"EIE2VBL3","created_at":"2026-07-05T11:08:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:EIE2VBL3DCMWX3KKNDLGW22VMG","target":"record","payload":{"canonical_record":{"source":{"id":"2410.15618","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-21T03:40:29Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"4160ba5839a94a5d80c9e2a58041294e1671d6b8852ce05d4d33a2f57384501d","abstract_canon_sha256":"743877f2cb06022bb65235201a98b832d66cebdcd573bea5fc8cea12b24c5bac"},"schema_version":"1.0"},"canonical_sha256":"2209aa857b18996bed4a68d66b6b556180c4dc60fe296ae13e50dbfe491e0f51","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:08:01.921381Z","signature_b64":"KQBRUtY94+OXVUxCPhtRh4CG9l8Id2i/SUnEZkh51eyIeibdLvT8J12FQnhE+fejbRFQBZR0f3twbaaSek1wDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2209aa857b18996bed4a68d66b6b556180c4dc60fe296ae13e50dbfe491e0f51","last_reissued_at":"2026-07-05T11:08:01.920833Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:08:01.920833Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.15618","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:08:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NJzPPPHCXfJrlTsoD02E2IavqxtH0BXfGGPstb2eLninrXfji7CJ6TO+FyXw4PFerY8xTz9mB40KsQppsnWICg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T00:23:32.929570Z"},"content_sha256":"2aa9003aa4cfd63c92c8bb13a3f1909509bb6a5319015a0e2a8172ce7e4ff0f0","schema_version":"1.0","event_id":"sha256:2aa9003aa4cfd63c92c8bb13a3f1909509bb6a5319015a0e2a8172ce7e4ff0f0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:EIE2VBL3DCMWX3KKNDLGW22VMG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Anh Bui, Dinh Phung, Khanh Doan, Long Vuong, Paul Montague, Tamas Abraham, Trung Le","submitted_at":"2024-10-21T03:40:29Z","abstract_excerpt":"Diffusion models excel at generating visually striking content from text but can inadvertently produce undesirable or harmful content when trained on unfiltered internet data. A practical solution is to selectively removing target concepts from the model, but this may impact the remaining concepts. Prior approaches have tried to balance this by introducing a loss term to preserve neutral content or a regularization term to minimize changes in the model parameters, yet resolving this trade-off remains challenging. In this work, we propose to identify and preserving concepts most affected by par"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.15618","kind":"arxiv","version":4},"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/2410.15618/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":"2026-07-05T11:08:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IHORbZnXen3UooKfiaBOd3fsVZRWhGL9IPc/rG2G/i0kZjtbcAzQKkEsopqaReZ/eXVAVJmCeqkFfHBFh2IIBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T00:23:32.930058Z"},"content_sha256":"4e78acc191a53eb9ecbe7613d878c2248a999ce35252377a5ece75e3811bebea","schema_version":"1.0","event_id":"sha256:4e78acc191a53eb9ecbe7613d878c2248a999ce35252377a5ece75e3811bebea"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EIE2VBL3DCMWX3KKNDLGW22VMG/bundle.json","state_url":"https://pith.science/pith/EIE2VBL3DCMWX3KKNDLGW22VMG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EIE2VBL3DCMWX3KKNDLGW22VMG/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":"2026-08-06T00:23:32Z","links":{"resolver":"https://pith.science/pith/EIE2VBL3DCMWX3KKNDLGW22VMG","bundle":"https://pith.science/pith/EIE2VBL3DCMWX3KKNDLGW22VMG/bundle.json","state":"https://pith.science/pith/EIE2VBL3DCMWX3KKNDLGW22VMG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EIE2VBL3DCMWX3KKNDLGW22VMG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:EIE2VBL3DCMWX3KKNDLGW22VMG","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":"743877f2cb06022bb65235201a98b832d66cebdcd573bea5fc8cea12b24c5bac","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-21T03:40:29Z","title_canon_sha256":"4160ba5839a94a5d80c9e2a58041294e1671d6b8852ce05d4d33a2f57384501d"},"schema_version":"1.0","source":{"id":"2410.15618","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.15618","created_at":"2026-07-05T11:08:01Z"},{"alias_kind":"arxiv_version","alias_value":"2410.15618v4","created_at":"2026-07-05T11:08:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.15618","created_at":"2026-07-05T11:08:01Z"},{"alias_kind":"pith_short_12","alias_value":"EIE2VBL3DCMW","created_at":"2026-07-05T11:08:01Z"},{"alias_kind":"pith_short_16","alias_value":"EIE2VBL3DCMWX3KK","created_at":"2026-07-05T11:08:01Z"},{"alias_kind":"pith_short_8","alias_value":"EIE2VBL3","created_at":"2026-07-05T11:08:01Z"}],"graph_snapshots":[{"event_id":"sha256:4e78acc191a53eb9ecbe7613d878c2248a999ce35252377a5ece75e3811bebea","target":"graph","created_at":"2026-07-05T11:08:01Z","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/2410.15618/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion models excel at generating visually striking content from text but can inadvertently produce undesirable or harmful content when trained on unfiltered internet data. A practical solution is to selectively removing target concepts from the model, but this may impact the remaining concepts. Prior approaches have tried to balance this by introducing a loss term to preserve neutral content or a regularization term to minimize changes in the model parameters, yet resolving this trade-off remains challenging. In this work, we propose to identify and preserving concepts most affected by par","authors_text":"Anh Bui, Dinh Phung, Khanh Doan, Long Vuong, Paul Montague, Tamas Abraham, Trung Le","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-21T03:40:29Z","title":"Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.15618","kind":"arxiv","version":4},"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":"sha256:2aa9003aa4cfd63c92c8bb13a3f1909509bb6a5319015a0e2a8172ce7e4ff0f0","target":"record","created_at":"2026-07-05T11:08:01Z","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":"743877f2cb06022bb65235201a98b832d66cebdcd573bea5fc8cea12b24c5bac","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-21T03:40:29Z","title_canon_sha256":"4160ba5839a94a5d80c9e2a58041294e1671d6b8852ce05d4d33a2f57384501d"},"schema_version":"1.0","source":{"id":"2410.15618","kind":"arxiv","version":4}},"canonical_sha256":"2209aa857b18996bed4a68d66b6b556180c4dc60fe296ae13e50dbfe491e0f51","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2209aa857b18996bed4a68d66b6b556180c4dc60fe296ae13e50dbfe491e0f51","first_computed_at":"2026-07-05T11:08:01.920833Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:08:01.920833Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KQBRUtY94+OXVUxCPhtRh4CG9l8Id2i/SUnEZkh51eyIeibdLvT8J12FQnhE+fejbRFQBZR0f3twbaaSek1wDw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:08:01.921381Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.15618","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2aa9003aa4cfd63c92c8bb13a3f1909509bb6a5319015a0e2a8172ce7e4ff0f0","sha256:4e78acc191a53eb9ecbe7613d878c2248a999ce35252377a5ece75e3811bebea"],"state_sha256":"deef87982fc4e2c60b7ae69f36cf1641ce58e726bffa7411e23900ef87e563f3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BhXUJad0KQkF0j35vbgVDBmQf4YLgdT5xh5JlbLmbdPn0nkv/MIddDyj7v0/2vCQzW7SV4UcF78cd76MnYqRCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T00:23:32.933570Z","bundle_sha256":"4a34af09deb385eb37c19dfa1cb20ceb2ac5cc0d9bfe82cef80c5560a931ee48"}}