{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:BVGCRLCXZNMBBUTDPOYVXXOJYU","short_pith_number":"pith:BVGCRLCX","canonical_record":{"source":{"id":"2607.23934","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-27T02:11:58Z","cross_cats_sorted":[],"title_canon_sha256":"32e9a763b390b0e4ad1eae956fb7b57e2a3dfc7431460f1a17dfb81cc3d3fa4b","abstract_canon_sha256":"8bae8800aee50bc7d71056c8967bcf5ae6dce1752d2b7eaaf4b1bf1efab4e991"},"schema_version":"1.0"},"canonical_sha256":"0d4c28ac57cb5810d2637bb15bddc9c51fe9399f07858c6115b7acf129017c8c","source":{"kind":"arxiv","id":"2607.23934","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.23934","created_at":"2026-07-28T01:23:36Z"},{"alias_kind":"arxiv_version","alias_value":"2607.23934v1","created_at":"2026-07-28T01:23:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.23934","created_at":"2026-07-28T01:23:36Z"},{"alias_kind":"pith_short_12","alias_value":"BVGCRLCXZNMB","created_at":"2026-07-28T01:23:36Z"},{"alias_kind":"pith_short_16","alias_value":"BVGCRLCXZNMBBUTD","created_at":"2026-07-28T01:23:36Z"},{"alias_kind":"pith_short_8","alias_value":"BVGCRLCX","created_at":"2026-07-28T01:23:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:BVGCRLCXZNMBBUTDPOYVXXOJYU","target":"record","payload":{"canonical_record":{"source":{"id":"2607.23934","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-27T02:11:58Z","cross_cats_sorted":[],"title_canon_sha256":"32e9a763b390b0e4ad1eae956fb7b57e2a3dfc7431460f1a17dfb81cc3d3fa4b","abstract_canon_sha256":"8bae8800aee50bc7d71056c8967bcf5ae6dce1752d2b7eaaf4b1bf1efab4e991"},"schema_version":"1.0"},"canonical_sha256":"0d4c28ac57cb5810d2637bb15bddc9c51fe9399f07858c6115b7acf129017c8c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-28T01:23:36.489380Z","signature_b64":"WBKF4NjX3WJwEJFGz7rr9Rs0rPuD66Fx5+sC5wFU9Zb7gr1XSv/AUIn4QHZe2Rwr927kmUlrdePMK5meLAicBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0d4c28ac57cb5810d2637bb15bddc9c51fe9399f07858c6115b7acf129017c8c","last_reissued_at":"2026-07-28T01:23:36.488539Z","signature_status":"signed_v1","first_computed_at":"2026-07-28T01:23:36.488539Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.23934","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-28T01:23:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tSXjqq1ANG/yuXnfQW4H0EfS7Q/F76VMafeS2wV3jDLVlKHe8rTKPYREI+1UM+ULzkITZ9h3t9S6Liui8wgKAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T21:41:33.818340Z"},"content_sha256":"84fa218f0b3c06338845349525f2d00fa9473235d6c6c33c5798c44d28dc68c8","schema_version":"1.0","event_id":"sha256:84fa218f0b3c06338845349525f2d00fa9473235d6c6c33c5798c44d28dc68c8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:BVGCRLCXZNMBBUTDPOYVXXOJYU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DECAF: De-Clustering for Adaptive Representational Unlearning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Anjie Le, Can Peng, Hongcheng Guo, J. Alison Noble","submitted_at":"2026-07-27T02:11:58Z","abstract_excerpt":"Machine unlearning, which aims to remove the influence of specific training data from a trained model, is a key requirement for privacy, accountability, and adaptive deployment. We argue that many unlearning methods are vulnerable to a simple clustering attack, which can recover class structure in an unsupervised manner, limiting their suitability for continual deployment where removal requests must be handled reliably on demand. To address this, we propose DECAF (DE-Clustering for Adaptive Forgetting), a post-hoc method that operates only on the forget set and is designed to break the cluster"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.23934","kind":"arxiv","version":1},"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/2607.23934/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":"2026-07-28T01:23:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nQaB7f15uG2xRS7GxAs3lws2HMTE7KAvyMeHnYbMSsQHUzU2PPOD++LOtyU35EFFjy/ldhm0UZ3yd+2wvJd9Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T21:41:33.818655Z"},"content_sha256":"f7089c1d1da8f98acbc5c9cee4a465a9493228512fa21caf86fdf4b60a05076b","schema_version":"1.0","event_id":"sha256:f7089c1d1da8f98acbc5c9cee4a465a9493228512fa21caf86fdf4b60a05076b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BVGCRLCXZNMBBUTDPOYVXXOJYU/bundle.json","state_url":"https://pith.science/pith/BVGCRLCXZNMBBUTDPOYVXXOJYU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BVGCRLCXZNMBBUTDPOYVXXOJYU/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":"2026-08-01T21:41:33Z","links":{"resolver":"https://pith.science/pith/BVGCRLCXZNMBBUTDPOYVXXOJYU","bundle":"https://pith.science/pith/BVGCRLCXZNMBBUTDPOYVXXOJYU/bundle.json","state":"https://pith.science/pith/BVGCRLCXZNMBBUTDPOYVXXOJYU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BVGCRLCXZNMBBUTDPOYVXXOJYU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:BVGCRLCXZNMBBUTDPOYVXXOJYU","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":"8bae8800aee50bc7d71056c8967bcf5ae6dce1752d2b7eaaf4b1bf1efab4e991","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-27T02:11:58Z","title_canon_sha256":"32e9a763b390b0e4ad1eae956fb7b57e2a3dfc7431460f1a17dfb81cc3d3fa4b"},"schema_version":"1.0","source":{"id":"2607.23934","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.23934","created_at":"2026-07-28T01:23:36Z"},{"alias_kind":"arxiv_version","alias_value":"2607.23934v1","created_at":"2026-07-28T01:23:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.23934","created_at":"2026-07-28T01:23:36Z"},{"alias_kind":"pith_short_12","alias_value":"BVGCRLCXZNMB","created_at":"2026-07-28T01:23:36Z"},{"alias_kind":"pith_short_16","alias_value":"BVGCRLCXZNMBBUTD","created_at":"2026-07-28T01:23:36Z"},{"alias_kind":"pith_short_8","alias_value":"BVGCRLCX","created_at":"2026-07-28T01:23:36Z"}],"graph_snapshots":[{"event_id":"sha256:f7089c1d1da8f98acbc5c9cee4a465a9493228512fa21caf86fdf4b60a05076b","target":"graph","created_at":"2026-07-28T01:23:36Z","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/2607.23934/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine unlearning, which aims to remove the influence of specific training data from a trained model, is a key requirement for privacy, accountability, and adaptive deployment. We argue that many unlearning methods are vulnerable to a simple clustering attack, which can recover class structure in an unsupervised manner, limiting their suitability for continual deployment where removal requests must be handled reliably on demand. To address this, we propose DECAF (DE-Clustering for Adaptive Forgetting), a post-hoc method that operates only on the forget set and is designed to break the cluster","authors_text":"Anjie Le, Can Peng, Hongcheng Guo, J. Alison Noble","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-27T02:11:58Z","title":"DECAF: De-Clustering for Adaptive Representational Unlearning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.23934","kind":"arxiv","version":1},"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":"sha256:84fa218f0b3c06338845349525f2d00fa9473235d6c6c33c5798c44d28dc68c8","target":"record","created_at":"2026-07-28T01:23:36Z","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":"8bae8800aee50bc7d71056c8967bcf5ae6dce1752d2b7eaaf4b1bf1efab4e991","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-27T02:11:58Z","title_canon_sha256":"32e9a763b390b0e4ad1eae956fb7b57e2a3dfc7431460f1a17dfb81cc3d3fa4b"},"schema_version":"1.0","source":{"id":"2607.23934","kind":"arxiv","version":1}},"canonical_sha256":"0d4c28ac57cb5810d2637bb15bddc9c51fe9399f07858c6115b7acf129017c8c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0d4c28ac57cb5810d2637bb15bddc9c51fe9399f07858c6115b7acf129017c8c","first_computed_at":"2026-07-28T01:23:36.488539Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-28T01:23:36.488539Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WBKF4NjX3WJwEJFGz7rr9Rs0rPuD66Fx5+sC5wFU9Zb7gr1XSv/AUIn4QHZe2Rwr927kmUlrdePMK5meLAicBA==","signature_status":"signed_v1","signed_at":"2026-07-28T01:23:36.489380Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.23934","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:84fa218f0b3c06338845349525f2d00fa9473235d6c6c33c5798c44d28dc68c8","sha256:f7089c1d1da8f98acbc5c9cee4a465a9493228512fa21caf86fdf4b60a05076b"],"state_sha256":"b39835ac9961e608a494e67edf08a9d9af5a0303d30a422da1ef9d45a4c0a732"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P5W7rSfpTw3cCpDaC3wWIYwaBYhufAPFkbzjVq+udxRpFMCffbD3RsbLlWwDMJo1maChGYpufVT78Y8hzh+QBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T21:41:33.821212Z","bundle_sha256":"3743ef8a417f90dfd58f5faeba3a5ff8cdf4d929f5b2d1c33961647cdd87d1c0"}}