{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:2T32PRORRK2LRPCTKONTBFEP5P","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":"ebf9e693e8efa23d68393e172b8df9cde928d457a74dc662afcd947dc06a47fb","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-04T18:01:59Z","title_canon_sha256":"2aca7b845ebcfc35d10e735b7c17513d5929c1fa937954782a520c419459dcc5"},"schema_version":"1.0","source":{"id":"2304.02049","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.02049","created_at":"2026-07-05T08:28:56Z"},{"alias_kind":"arxiv_version","alias_value":"2304.02049v2","created_at":"2026-07-05T08:28:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.02049","created_at":"2026-07-05T08:28:56Z"},{"alias_kind":"pith_short_12","alias_value":"2T32PRORRK2L","created_at":"2026-07-05T08:28:56Z"},{"alias_kind":"pith_short_16","alias_value":"2T32PRORRK2LRPCT","created_at":"2026-07-05T08:28:56Z"},{"alias_kind":"pith_short_8","alias_value":"2T32PROR","created_at":"2026-07-05T08:28:56Z"}],"graph_snapshots":[{"event_id":"sha256:dcc6c2cca30bf14d03e7c0b308bf7a852875f3c204c6d84257cc21ea85b95397","target":"graph","created_at":"2026-07-05T08:28:56Z","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/2304.02049/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine Unlearning is an emerging paradigm for selectively removing the impact of training datapoints from a network. Unlike existing methods that target a limited subset or a single class, our framework unlearns all classes in a single round. We achieve this by modulating the network's components using memory matrices, enabling the network to demonstrate selective unlearning behavior for any class after training. By discovering weights that are specific to each class, our approach also recovers a representation of the classes which is explainable by design. We test the proposed framework on s","authors_text":"Lorenzo Baraldi, Marcella Cornia, Rita Cucchiara, Samuele Poppi, Sara Sarto","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-04T18:01:59Z","title":"Multi-Class Unlearning for Image Classification via Weight Filtering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.02049","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":"sha256:794e1ae26b896ca3f3d9be0cea2984b11744af47fcdedc95663d10dca05b77c3","target":"record","created_at":"2026-07-05T08:28:56Z","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":"ebf9e693e8efa23d68393e172b8df9cde928d457a74dc662afcd947dc06a47fb","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-04T18:01:59Z","title_canon_sha256":"2aca7b845ebcfc35d10e735b7c17513d5929c1fa937954782a520c419459dcc5"},"schema_version":"1.0","source":{"id":"2304.02049","kind":"arxiv","version":2}},"canonical_sha256":"d4f7a7c5d18ab4b8bc53539b30948febfca84890e8d38626b65db6cafc63989f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d4f7a7c5d18ab4b8bc53539b30948febfca84890e8d38626b65db6cafc63989f","first_computed_at":"2026-07-05T08:28:56.396022Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:28:56.396022Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vT2c8xkElqyi2ZXZUHsEKu1QsPddXWPH/znwAC6sM+Rc0ExISujbOSYQdx2l6Zbwy5vF8DGRH6IiMOuYK8RqDw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:28:56.396484Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.02049","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:794e1ae26b896ca3f3d9be0cea2984b11744af47fcdedc95663d10dca05b77c3","sha256:dcc6c2cca30bf14d03e7c0b308bf7a852875f3c204c6d84257cc21ea85b95397"],"state_sha256":"526ea586eb9f7493c70a28df1b24cfd2d31f5616b084b44ec7a094838ee3904f"}