{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:6ALA4TNO2BUOYSALPHU7BLZW7Z","short_pith_number":"pith:6ALA4TNO","canonical_record":{"source":{"id":"2506.06985","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-08T03:55:28Z","cross_cats_sorted":["cs.CR","stat.ML"],"title_canon_sha256":"64fb7d45a716e6b6ab8381c5ecf1620f95e1f30134d3aa0c21fdae916e7fa648","abstract_canon_sha256":"199e7a5b6e7e754ec1455d8a0ae292d286fefaf00e5d18e73e71d01d59bec2b1"},"schema_version":"1.0"},"canonical_sha256":"f0160e4daed068ec480b79e9f0af36fe786bebb3cdb5e9f3c1971b8b940c8a4f","source":{"kind":"arxiv","id":"2506.06985","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.06985","created_at":"2026-07-05T11:19:28Z"},{"alias_kind":"arxiv_version","alias_value":"2506.06985v2","created_at":"2026-07-05T11:19:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.06985","created_at":"2026-07-05T11:19:28Z"},{"alias_kind":"pith_short_12","alias_value":"6ALA4TNO2BUO","created_at":"2026-07-05T11:19:28Z"},{"alias_kind":"pith_short_16","alias_value":"6ALA4TNO2BUOYSAL","created_at":"2026-07-05T11:19:28Z"},{"alias_kind":"pith_short_8","alias_value":"6ALA4TNO","created_at":"2026-07-05T11:19:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:6ALA4TNO2BUOYSALPHU7BLZW7Z","target":"record","payload":{"canonical_record":{"source":{"id":"2506.06985","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-08T03:55:28Z","cross_cats_sorted":["cs.CR","stat.ML"],"title_canon_sha256":"64fb7d45a716e6b6ab8381c5ecf1620f95e1f30134d3aa0c21fdae916e7fa648","abstract_canon_sha256":"199e7a5b6e7e754ec1455d8a0ae292d286fefaf00e5d18e73e71d01d59bec2b1"},"schema_version":"1.0"},"canonical_sha256":"f0160e4daed068ec480b79e9f0af36fe786bebb3cdb5e9f3c1971b8b940c8a4f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:19:28.625298Z","signature_b64":"qPVWt7/S6igP9yV0XuIj1lLs785TecyK7TLSnai+T/xWdi83HzjzhhyBlXvOwJXFewVbXkEu5fAJR7+9SNhdDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f0160e4daed068ec480b79e9f0af36fe786bebb3cdb5e9f3c1971b8b940c8a4f","last_reissued_at":"2026-07-05T11:19:28.624722Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:19:28.624722Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.06985","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":"2026-07-05T11:19:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PC78GHB6ADh4WiGANJ5gB2F8e5+YmjgBb7GnZUrtNxQBJIdjLLdT5blXmMrQflI1iBwhIHfrmfuICtFbqyiZBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T12:29:29.796933Z"},"content_sha256":"d389e18e86752ed299a601401689b27f9d6dc17c9ce6441666d537f96845e9cc","schema_version":"1.0","event_id":"sha256:d389e18e86752ed299a601401689b27f9d6dc17c9ce6441666d537f96845e9cc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:6ALA4TNO2BUOYSALPHU7BLZW7Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Certified Unlearning for Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","stat.ML"],"primary_cat":"cs.LG","authors_text":"Anastasia Koloskova, Animesh Jha, Rachid Guerraoui, Sanmi Koyejo, Youssef Allouah","submitted_at":"2025-06-08T03:55:28Z","abstract_excerpt":"We address the problem of machine unlearning, where the goal is to remove the influence of specific training data from a model upon request, motivated by privacy concerns and regulatory requirements such as the \"right to be forgotten.\" Unfortunately, existing methods rely on restrictive assumptions or lack formal guarantees. To this end, we propose a novel method for certified machine unlearning, leveraging the connection between unlearning and privacy amplification by stochastic post-processing. Our method uses noisy fine-tuning on the retain data, i.e., data that does not need to be removed,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.06985","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/2506.06985/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":"2026-07-05T11:19:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q64AG5PsiUTjs5SslQwCVF9Fo+DJKucfnB++2u09mjT3PlhaKhAQdswcA03jeHWZjFNlpCcRHD1CCfqiNyASCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T12:29:29.797452Z"},"content_sha256":"10757ac225ef3df7b43b2d552ab0a60cc25a212bd8cfaf179aae47f2d0cd280d","schema_version":"1.0","event_id":"sha256:10757ac225ef3df7b43b2d552ab0a60cc25a212bd8cfaf179aae47f2d0cd280d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6ALA4TNO2BUOYSALPHU7BLZW7Z/bundle.json","state_url":"https://pith.science/pith/6ALA4TNO2BUOYSALPHU7BLZW7Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6ALA4TNO2BUOYSALPHU7BLZW7Z/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":"2026-08-09T12:29:29Z","links":{"resolver":"https://pith.science/pith/6ALA4TNO2BUOYSALPHU7BLZW7Z","bundle":"https://pith.science/pith/6ALA4TNO2BUOYSALPHU7BLZW7Z/bundle.json","state":"https://pith.science/pith/6ALA4TNO2BUOYSALPHU7BLZW7Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6ALA4TNO2BUOYSALPHU7BLZW7Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:6ALA4TNO2BUOYSALPHU7BLZW7Z","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":"199e7a5b6e7e754ec1455d8a0ae292d286fefaf00e5d18e73e71d01d59bec2b1","cross_cats_sorted":["cs.CR","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-08T03:55:28Z","title_canon_sha256":"64fb7d45a716e6b6ab8381c5ecf1620f95e1f30134d3aa0c21fdae916e7fa648"},"schema_version":"1.0","source":{"id":"2506.06985","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.06985","created_at":"2026-07-05T11:19:28Z"},{"alias_kind":"arxiv_version","alias_value":"2506.06985v2","created_at":"2026-07-05T11:19:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.06985","created_at":"2026-07-05T11:19:28Z"},{"alias_kind":"pith_short_12","alias_value":"6ALA4TNO2BUO","created_at":"2026-07-05T11:19:28Z"},{"alias_kind":"pith_short_16","alias_value":"6ALA4TNO2BUOYSAL","created_at":"2026-07-05T11:19:28Z"},{"alias_kind":"pith_short_8","alias_value":"6ALA4TNO","created_at":"2026-07-05T11:19:28Z"}],"graph_snapshots":[{"event_id":"sha256:10757ac225ef3df7b43b2d552ab0a60cc25a212bd8cfaf179aae47f2d0cd280d","target":"graph","created_at":"2026-07-05T11:19:28Z","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/2506.06985/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We address the problem of machine unlearning, where the goal is to remove the influence of specific training data from a model upon request, motivated by privacy concerns and regulatory requirements such as the \"right to be forgotten.\" Unfortunately, existing methods rely on restrictive assumptions or lack formal guarantees. To this end, we propose a novel method for certified machine unlearning, leveraging the connection between unlearning and privacy amplification by stochastic post-processing. Our method uses noisy fine-tuning on the retain data, i.e., data that does not need to be removed,","authors_text":"Anastasia Koloskova, Animesh Jha, Rachid Guerraoui, Sanmi Koyejo, Youssef Allouah","cross_cats":["cs.CR","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-08T03:55:28Z","title":"Certified Unlearning for Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.06985","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:d389e18e86752ed299a601401689b27f9d6dc17c9ce6441666d537f96845e9cc","target":"record","created_at":"2026-07-05T11:19:28Z","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":"199e7a5b6e7e754ec1455d8a0ae292d286fefaf00e5d18e73e71d01d59bec2b1","cross_cats_sorted":["cs.CR","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-08T03:55:28Z","title_canon_sha256":"64fb7d45a716e6b6ab8381c5ecf1620f95e1f30134d3aa0c21fdae916e7fa648"},"schema_version":"1.0","source":{"id":"2506.06985","kind":"arxiv","version":2}},"canonical_sha256":"f0160e4daed068ec480b79e9f0af36fe786bebb3cdb5e9f3c1971b8b940c8a4f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f0160e4daed068ec480b79e9f0af36fe786bebb3cdb5e9f3c1971b8b940c8a4f","first_computed_at":"2026-07-05T11:19:28.624722Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:19:28.624722Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qPVWt7/S6igP9yV0XuIj1lLs785TecyK7TLSnai+T/xWdi83HzjzhhyBlXvOwJXFewVbXkEu5fAJR7+9SNhdDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:19:28.625298Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.06985","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d389e18e86752ed299a601401689b27f9d6dc17c9ce6441666d537f96845e9cc","sha256:10757ac225ef3df7b43b2d552ab0a60cc25a212bd8cfaf179aae47f2d0cd280d"],"state_sha256":"ccf17720c5c7508840aa302b3e8886ff3dbbd354f2563acab03e7fb794665737"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iPsLgGG+aGuVlkQfeetqBhhT77q/Y7dOtznSabfdy3ULm9zxRgfVWLXkrsjdHMSYrhZcAozkZriadaF/Cvt8Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T12:29:29.803097Z","bundle_sha256":"7d5c49abcf55bec472808e884013b992c8af8055a64a7bbf3c98811061393df8"}}