{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:2U3ZABGJDR7RHMSCJSRFHTHXFM","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":"90b0ac4743ef260b2ab8d19ba615e31f6c117c64570dc512b301aa910585a884","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-20T10:15:36Z","title_canon_sha256":"9dd14f83cca03623a72ca10c6eaec2334b01a24468867fb5db64ba729d0552c2"},"schema_version":"1.0","source":{"id":"2302.09880","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.09880","created_at":"2026-07-05T07:06:23Z"},{"alias_kind":"arxiv_version","alias_value":"2302.09880v3","created_at":"2026-07-05T07:06:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.09880","created_at":"2026-07-05T07:06:23Z"},{"alias_kind":"pith_short_12","alias_value":"2U3ZABGJDR7R","created_at":"2026-07-05T07:06:23Z"},{"alias_kind":"pith_short_16","alias_value":"2U3ZABGJDR7RHMSC","created_at":"2026-07-05T07:06:23Z"},{"alias_kind":"pith_short_8","alias_value":"2U3ZABGJ","created_at":"2026-07-05T07:06:23Z"}],"graph_snapshots":[{"event_id":"sha256:e3ecd12646b50304a9dc33605bc22b47a0dd0d7d5b644f012122cdbd8393c431","target":"graph","created_at":"2026-07-05T07:06:23Z","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/2302.09880/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep machine unlearning is the problem of `removing' from a trained neural network a subset of its training set. This problem is very timely and has many applications, including the key tasks of removing biases (RB), resolving confusion (RC) (caused by mislabelled data in trained models), as well as allowing users to exercise their `right to be forgotten' to protect User Privacy (UP). This paper is the first, to our knowledge, to study unlearning for different applications (RB, RC, UP), with the view that each has its own desiderata, definitions for `forgetting' and associated metrics for forg","authors_text":"Eleni Triantafillou, Jamie Hayes, Meghdad Kurmanji, Peter Triantafillou","cross_cats":["cs.CR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-20T10:15:36Z","title":"Towards Unbounded Machine Unlearning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.09880","kind":"arxiv","version":3},"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":"sha256:20b77fdbc416e5aa667ccc9aea58a8cf1c43cf3f0012f9b93264153e29a8f0d1","target":"record","created_at":"2026-07-05T07:06:23Z","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":"90b0ac4743ef260b2ab8d19ba615e31f6c117c64570dc512b301aa910585a884","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-20T10:15:36Z","title_canon_sha256":"9dd14f83cca03623a72ca10c6eaec2334b01a24468867fb5db64ba729d0552c2"},"schema_version":"1.0","source":{"id":"2302.09880","kind":"arxiv","version":3}},"canonical_sha256":"d5379004c91c7f13b2424ca253ccf72b28032b5c94f8a83e5bec7aa467a1bc73","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d5379004c91c7f13b2424ca253ccf72b28032b5c94f8a83e5bec7aa467a1bc73","first_computed_at":"2026-07-05T07:06:23.521277Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:06:23.521277Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ib+8kHVmrHyKSqcSUQR+/perduwI2MD3EiO9h0jGr9kBlMG6RFlKdFGW0qAaJzjvKAMzWDHeXfm3b/adjqRVAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:06:23.521783Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.09880","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:20b77fdbc416e5aa667ccc9aea58a8cf1c43cf3f0012f9b93264153e29a8f0d1","sha256:e3ecd12646b50304a9dc33605bc22b47a0dd0d7d5b644f012122cdbd8393c431"],"state_sha256":"9454b66c20ce64ee7a32711eb979c5cf0ec81bef4c45cba542a11cfa3a55cda8"}