{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:RNNTZ6FKU7EBWHOQ2YVNHGV5YW","short_pith_number":"pith:RNNTZ6FK","canonical_record":{"source":{"id":"2410.13850","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T17:59:02Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"3ff47f2cdc8c786b04e3af95efe13c0818b93eb4fad17fb0fc64be8fa07ce48f","abstract_canon_sha256":"97c615af68966df11047cb794efe2509aedc15e4f8fdc9a7464b69581b495b9b"},"schema_version":"1.0"},"canonical_sha256":"8b5b3cf8aaa7c81b1dd0d62ad39abdc5b2b830533c7698fc935a6cc8e0ab0c6a","source":{"kind":"arxiv","id":"2410.13850","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.13850","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"arxiv_version","alias_value":"2410.13850v5","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.13850","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_12","alias_value":"RNNTZ6FKU7EB","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_16","alias_value":"RNNTZ6FKU7EBWHOQ","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_8","alias_value":"RNNTZ6FK","created_at":"2026-07-05T11:09:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:RNNTZ6FKU7EBWHOQ2YVNHGV5YW","target":"record","payload":{"canonical_record":{"source":{"id":"2410.13850","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T17:59:02Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"3ff47f2cdc8c786b04e3af95efe13c0818b93eb4fad17fb0fc64be8fa07ce48f","abstract_canon_sha256":"97c615af68966df11047cb794efe2509aedc15e4f8fdc9a7464b69581b495b9b"},"schema_version":"1.0"},"canonical_sha256":"8b5b3cf8aaa7c81b1dd0d62ad39abdc5b2b830533c7698fc935a6cc8e0ab0c6a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:09:01.795466Z","signature_b64":"D86wcYcB8WEF7b7eFuAj7dDeca/llPvQfGGByCHtFrwBOMkI4Ig6pjqKb5t3t+edNrr9jVMvPg7fG3Dy7kYLCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8b5b3cf8aaa7c81b1dd0d62ad39abdc5b2b830533c7698fc935a6cc8e0ab0c6a","last_reissued_at":"2026-07-05T11:09:01.794987Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:09:01.794987Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.13850","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:09:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VYnf3BSViZmz5ymf3jcWi397BhYGrz/+F5frY+9BlQpEM8ddy3faGW8RN5SndfgI/9IRT3d4rr9OLZWAqaA6Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-26T23:42:39.428466Z"},"content_sha256":"dfe30fa211c7a71c041c3369e9e33a8d55cc4e860fe071ab1570c1d6780fb022","schema_version":"1.0","event_id":"sha256:dfe30fa211c7a71c041c3369e9e33a8d55cc4e860fe071ab1570c1d6780fb022"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:RNNTZ6FKU7EBWHOQ2YVNHGV5YW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Influence Functions for Scalable Data Attribution in Diffusion Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Alexander Immer, Bruno Mlodozeniec, David Krueger, Juhan Bae, Richard Turner, Runa Eschenhagen","submitted_at":"2024-10-17T17:59:02Z","abstract_excerpt":"Diffusion models have led to significant advancements in generative modelling. Yet their widespread adoption poses challenges regarding data attribution and interpretability. In this paper, we aim to help address such challenges in diffusion models by developing an influence functions framework. Influence function-based data attribution methods approximate how a model's output would have changed if some training data were removed. In supervised learning, this is usually used for predicting how the loss on a particular example would change. For diffusion models, we focus on predicting the chang"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.13850","kind":"arxiv","version":5},"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/2410.13850/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":"2026-07-05T11:09:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ouuw3nODxr6nhFaxKHMb072zUv3v2CcugFgYBvKI+4ctpwf8HMuetC43Paw+ul4c28cAcx6vQ4bUenmFX5VjCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-26T23:42:39.428850Z"},"content_sha256":"37b31d601bd58b4173928a9e61dfe5405d4ea78e75d95ab39fcd243c099bf581","schema_version":"1.0","event_id":"sha256:37b31d601bd58b4173928a9e61dfe5405d4ea78e75d95ab39fcd243c099bf581"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RNNTZ6FKU7EBWHOQ2YVNHGV5YW/bundle.json","state_url":"https://pith.science/pith/RNNTZ6FKU7EBWHOQ2YVNHGV5YW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RNNTZ6FKU7EBWHOQ2YVNHGV5YW/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":"2026-07-26T23:42:39Z","links":{"resolver":"https://pith.science/pith/RNNTZ6FKU7EBWHOQ2YVNHGV5YW","bundle":"https://pith.science/pith/RNNTZ6FKU7EBWHOQ2YVNHGV5YW/bundle.json","state":"https://pith.science/pith/RNNTZ6FKU7EBWHOQ2YVNHGV5YW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RNNTZ6FKU7EBWHOQ2YVNHGV5YW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:RNNTZ6FKU7EBWHOQ2YVNHGV5YW","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":"97c615af68966df11047cb794efe2509aedc15e4f8fdc9a7464b69581b495b9b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T17:59:02Z","title_canon_sha256":"3ff47f2cdc8c786b04e3af95efe13c0818b93eb4fad17fb0fc64be8fa07ce48f"},"schema_version":"1.0","source":{"id":"2410.13850","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.13850","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"arxiv_version","alias_value":"2410.13850v5","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.13850","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_12","alias_value":"RNNTZ6FKU7EB","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_16","alias_value":"RNNTZ6FKU7EBWHOQ","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_8","alias_value":"RNNTZ6FK","created_at":"2026-07-05T11:09:01Z"}],"graph_snapshots":[{"event_id":"sha256:37b31d601bd58b4173928a9e61dfe5405d4ea78e75d95ab39fcd243c099bf581","target":"graph","created_at":"2026-07-05T11:09:01Z","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/2410.13850/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion models have led to significant advancements in generative modelling. Yet their widespread adoption poses challenges regarding data attribution and interpretability. In this paper, we aim to help address such challenges in diffusion models by developing an influence functions framework. Influence function-based data attribution methods approximate how a model's output would have changed if some training data were removed. In supervised learning, this is usually used for predicting how the loss on a particular example would change. For diffusion models, we focus on predicting the chang","authors_text":"Alexander Immer, Bruno Mlodozeniec, David Krueger, Juhan Bae, Richard Turner, Runa Eschenhagen","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T17:59:02Z","title":"Influence Functions for Scalable Data Attribution in Diffusion Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.13850","kind":"arxiv","version":5},"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:dfe30fa211c7a71c041c3369e9e33a8d55cc4e860fe071ab1570c1d6780fb022","target":"record","created_at":"2026-07-05T11:09:01Z","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":"97c615af68966df11047cb794efe2509aedc15e4f8fdc9a7464b69581b495b9b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T17:59:02Z","title_canon_sha256":"3ff47f2cdc8c786b04e3af95efe13c0818b93eb4fad17fb0fc64be8fa07ce48f"},"schema_version":"1.0","source":{"id":"2410.13850","kind":"arxiv","version":5}},"canonical_sha256":"8b5b3cf8aaa7c81b1dd0d62ad39abdc5b2b830533c7698fc935a6cc8e0ab0c6a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8b5b3cf8aaa7c81b1dd0d62ad39abdc5b2b830533c7698fc935a6cc8e0ab0c6a","first_computed_at":"2026-07-05T11:09:01.794987Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:09:01.794987Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"D86wcYcB8WEF7b7eFuAj7dDeca/llPvQfGGByCHtFrwBOMkI4Ig6pjqKb5t3t+edNrr9jVMvPg7fG3Dy7kYLCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:09:01.795466Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.13850","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dfe30fa211c7a71c041c3369e9e33a8d55cc4e860fe071ab1570c1d6780fb022","sha256:37b31d601bd58b4173928a9e61dfe5405d4ea78e75d95ab39fcd243c099bf581"],"state_sha256":"a59080619be15d00b594fc5c628ee5120f5ecdb425778f758bb0051d1e43da34"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tcnwNKLzG8tqQ0D5i89PZ0KYWRwbvs3saFjs9kwmtSiWrQj1rYLQ0nE9Qm22h4noH0AcmRaYnbVvbAIsIbS9BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-26T23:42:39.430987Z","bundle_sha256":"03285292737c43737ddfa8033331bc2a12f6edc3e905484c22a0b53b0e0a97b4"}}