{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:YOCIMWIVGVDOCTAAWBL5IHKMKH","short_pith_number":"pith:YOCIMWIV","canonical_record":{"source":{"id":"2601.04275","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CR","submitted_at":"2026-01-07T12:11:25Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"df68abe72246c684550425239d6edea89f8fc7b2bf7c3110bf2ee71fa60393ec","abstract_canon_sha256":"10c8e5f26188de3b36fd4c961e7d8cd0af6dd052c44ed35482d434f4c6612c9f"},"schema_version":"1.0"},"canonical_sha256":"c3848659153546e14c00b057d41d4c51e9bac2698930a90fb32e1bced497eade","source":{"kind":"arxiv","id":"2601.04275","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.04275","created_at":"2026-05-27T01:05:42Z"},{"alias_kind":"arxiv_version","alias_value":"2601.04275v2","created_at":"2026-05-27T01:05:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.04275","created_at":"2026-05-27T01:05:42Z"},{"alias_kind":"pith_short_12","alias_value":"YOCIMWIVGVDO","created_at":"2026-05-27T01:05:42Z"},{"alias_kind":"pith_short_16","alias_value":"YOCIMWIVGVDOCTAA","created_at":"2026-05-27T01:05:42Z"},{"alias_kind":"pith_short_8","alias_value":"YOCIMWIV","created_at":"2026-05-27T01:05:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:YOCIMWIVGVDOCTAAWBL5IHKMKH","target":"record","payload":{"canonical_record":{"source":{"id":"2601.04275","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CR","submitted_at":"2026-01-07T12:11:25Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"df68abe72246c684550425239d6edea89f8fc7b2bf7c3110bf2ee71fa60393ec","abstract_canon_sha256":"10c8e5f26188de3b36fd4c961e7d8cd0af6dd052c44ed35482d434f4c6612c9f"},"schema_version":"1.0"},"canonical_sha256":"c3848659153546e14c00b057d41d4c51e9bac2698930a90fb32e1bced497eade","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-27T01:05:42.181686Z","signature_b64":"ods3b9C8KnLU0Rz9Aa74qvs7gMX9Jf2nGopy4pMTOc9L3kDWZehuYgPVwdv/RSLTBFlo1797SH/PplQvQiIGDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c3848659153546e14c00b057d41d4c51e9bac2698930a90fb32e1bced497eade","last_reissued_at":"2026-05-27T01:05:42.181018Z","signature_status":"signed_v1","first_computed_at":"2026-05-27T01:05:42.181018Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2601.04275","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":"2026-05-27T01:05:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KA//FYZGetRUJ2iVszDr02bUjvI4IxYvpYGvr18T//7eetNohQ4JqIumqr0DnapEZn2mCHRyNDRYWWbzZ9qxAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T02:14:00.695118Z"},"content_sha256":"ba30af724dec9ffdc85269b753c4988a76879412e3cb1e99cd8ca3872ec914a5","schema_version":"1.0","event_id":"sha256:ba30af724dec9ffdc85269b753c4988a76879412e3cb1e99cd8ca3872ec914a5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:YOCIMWIVGVDOCTAAWBL5IHKMKH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Shadow Unlearning: A Neuro-Semantic Approach to Fidelity-Preserving Faceless Forgetting in LLMs","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.CR","authors_text":"Ashok Urlana, Bala Mallikarjunarao Garlapati, Dinesh Srivasthav P, Ponnurangam Kumaraguru, Rahul Mishra","submitted_at":"2026-01-07T12:11:25Z","abstract_excerpt":"Machine unlearning aims to selectively remove the influence of specific training samples to satisfy privacy regulations such as the GDPR's 'Right to be Forgotten'. However, many existing methods require access to the data being removed, exposing it to membership inference attacks and potential misuse of Personally Identifiable Information (PII). We address this critical challenge by proposing Shadow Unlearning, a novel paradigm of approximate unlearning, that performs machine unlearning on anonymized forget data without exposing PII. We further propose a novel privacy-preserving framework, Neu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.04275","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/2601.04275/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":"2026-05-27T01:05:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vR7DHPjkMI7s5k50D/QT/IC0E6Df91ckFpwBZM/kEsT7pVu1JDga+R6xP8TjZWPiiicqNEvLCB3L0CJjYFKyBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T02:14:00.695759Z"},"content_sha256":"7a3b665e74095a0bfe292ed3df4742350d918dcdf61e1fc6a565f0b5ec73aed6","schema_version":"1.0","event_id":"sha256:7a3b665e74095a0bfe292ed3df4742350d918dcdf61e1fc6a565f0b5ec73aed6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YOCIMWIVGVDOCTAAWBL5IHKMKH/bundle.json","state_url":"https://pith.science/pith/YOCIMWIVGVDOCTAAWBL5IHKMKH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YOCIMWIVGVDOCTAAWBL5IHKMKH/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":"2026-06-05T02:14:00Z","links":{"resolver":"https://pith.science/pith/YOCIMWIVGVDOCTAAWBL5IHKMKH","bundle":"https://pith.science/pith/YOCIMWIVGVDOCTAAWBL5IHKMKH/bundle.json","state":"https://pith.science/pith/YOCIMWIVGVDOCTAAWBL5IHKMKH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YOCIMWIVGVDOCTAAWBL5IHKMKH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:YOCIMWIVGVDOCTAAWBL5IHKMKH","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":"10c8e5f26188de3b36fd4c961e7d8cd0af6dd052c44ed35482d434f4c6612c9f","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CR","submitted_at":"2026-01-07T12:11:25Z","title_canon_sha256":"df68abe72246c684550425239d6edea89f8fc7b2bf7c3110bf2ee71fa60393ec"},"schema_version":"1.0","source":{"id":"2601.04275","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.04275","created_at":"2026-05-27T01:05:42Z"},{"alias_kind":"arxiv_version","alias_value":"2601.04275v2","created_at":"2026-05-27T01:05:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.04275","created_at":"2026-05-27T01:05:42Z"},{"alias_kind":"pith_short_12","alias_value":"YOCIMWIVGVDO","created_at":"2026-05-27T01:05:42Z"},{"alias_kind":"pith_short_16","alias_value":"YOCIMWIVGVDOCTAA","created_at":"2026-05-27T01:05:42Z"},{"alias_kind":"pith_short_8","alias_value":"YOCIMWIV","created_at":"2026-05-27T01:05:42Z"}],"graph_snapshots":[{"event_id":"sha256:7a3b665e74095a0bfe292ed3df4742350d918dcdf61e1fc6a565f0b5ec73aed6","target":"graph","created_at":"2026-05-27T01:05:42Z","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/2601.04275/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine unlearning aims to selectively remove the influence of specific training samples to satisfy privacy regulations such as the GDPR's 'Right to be Forgotten'. However, many existing methods require access to the data being removed, exposing it to membership inference attacks and potential misuse of Personally Identifiable Information (PII). We address this critical challenge by proposing Shadow Unlearning, a novel paradigm of approximate unlearning, that performs machine unlearning on anonymized forget data without exposing PII. We further propose a novel privacy-preserving framework, Neu","authors_text":"Ashok Urlana, Bala Mallikarjunarao Garlapati, Dinesh Srivasthav P, Ponnurangam Kumaraguru, Rahul Mishra","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CR","submitted_at":"2026-01-07T12:11:25Z","title":"Shadow Unlearning: A Neuro-Semantic Approach to Fidelity-Preserving Faceless Forgetting in LLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.04275","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:ba30af724dec9ffdc85269b753c4988a76879412e3cb1e99cd8ca3872ec914a5","target":"record","created_at":"2026-05-27T01:05:42Z","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":"10c8e5f26188de3b36fd4c961e7d8cd0af6dd052c44ed35482d434f4c6612c9f","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CR","submitted_at":"2026-01-07T12:11:25Z","title_canon_sha256":"df68abe72246c684550425239d6edea89f8fc7b2bf7c3110bf2ee71fa60393ec"},"schema_version":"1.0","source":{"id":"2601.04275","kind":"arxiv","version":2}},"canonical_sha256":"c3848659153546e14c00b057d41d4c51e9bac2698930a90fb32e1bced497eade","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c3848659153546e14c00b057d41d4c51e9bac2698930a90fb32e1bced497eade","first_computed_at":"2026-05-27T01:05:42.181018Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-27T01:05:42.181018Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ods3b9C8KnLU0Rz9Aa74qvs7gMX9Jf2nGopy4pMTOc9L3kDWZehuYgPVwdv/RSLTBFlo1797SH/PplQvQiIGDA==","signature_status":"signed_v1","signed_at":"2026-05-27T01:05:42.181686Z","signed_message":"canonical_sha256_bytes"},"source_id":"2601.04275","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ba30af724dec9ffdc85269b753c4988a76879412e3cb1e99cd8ca3872ec914a5","sha256:7a3b665e74095a0bfe292ed3df4742350d918dcdf61e1fc6a565f0b5ec73aed6"],"state_sha256":"6fa603dfc10a0cf45ee4468cb114b07d8a716adef0c8fa2c19d8021d1644f1cd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ciGJUZSHxaSoWBniY9bSLOr7HJGsw8nfaAs4bpoekQCExx2RO7VsomtDSZiIeuTtDSsv+GEc0XSh1byuzSEsAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T02:14:00.698625Z","bundle_sha256":"19585f4c972c51306df8082eff3c00795b819b695cf1a842ec99f0439787befb"}}