{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:SL447NJTJIU2DFYRQLIJYXFARC","short_pith_number":"pith:SL447NJT","canonical_record":{"source":{"id":"2509.12958","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-09-16T11:01:59Z","cross_cats_sorted":[],"title_canon_sha256":"5a673e03ca4beede9b5b02d43715e59652095c1cdf7a7e988b2018214a904aa5","abstract_canon_sha256":"ae2b023409ca97433fa47292bc60518e90eb17efb2f6e908e4a7ecb555a38e91"},"schema_version":"1.0"},"canonical_sha256":"92f9cfb5334a29a1971182d09c5ca088a718101108dd2d1e7630da6c8172d053","source":{"kind":"arxiv","id":"2509.12958","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.12958","created_at":"2026-05-25T02:01:07Z"},{"alias_kind":"arxiv_version","alias_value":"2509.12958v2","created_at":"2026-05-25T02:01:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.12958","created_at":"2026-05-25T02:01:07Z"},{"alias_kind":"pith_short_12","alias_value":"SL447NJTJIU2","created_at":"2026-05-25T02:01:07Z"},{"alias_kind":"pith_short_16","alias_value":"SL447NJTJIU2DFYR","created_at":"2026-05-25T02:01:07Z"},{"alias_kind":"pith_short_8","alias_value":"SL447NJT","created_at":"2026-05-25T02:01:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:SL447NJTJIU2DFYRQLIJYXFARC","target":"record","payload":{"canonical_record":{"source":{"id":"2509.12958","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-09-16T11:01:59Z","cross_cats_sorted":[],"title_canon_sha256":"5a673e03ca4beede9b5b02d43715e59652095c1cdf7a7e988b2018214a904aa5","abstract_canon_sha256":"ae2b023409ca97433fa47292bc60518e90eb17efb2f6e908e4a7ecb555a38e91"},"schema_version":"1.0"},"canonical_sha256":"92f9cfb5334a29a1971182d09c5ca088a718101108dd2d1e7630da6c8172d053","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-25T02:01:07.165142Z","signature_b64":"8PZqrIekcyIH6adnujzq1Bi+YbjWKP2JUkz8dR7TbXHdynBDAAB9wDpiPQNe1HaTajsRf7gAMw0RsOx9ZwfCDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"92f9cfb5334a29a1971182d09c5ca088a718101108dd2d1e7630da6c8172d053","last_reissued_at":"2026-05-25T02:01:07.164300Z","signature_status":"signed_v1","first_computed_at":"2026-05-25T02:01:07.164300Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2509.12958","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":"2026-05-25T02:01:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0W6ryQPGOWWVAzAmh7Mz3NRb4/JOQX/95+XW22OFdaSD5vew99Na50vd4w7PLFp2fOHs8KqH7tRuFFhCIwL3Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T23:07:00.200469Z"},"content_sha256":"a43109bbeabf7f445a56e9b053396c7d9ac4a488acb068775ba4395d6ef95288","schema_version":"1.0","event_id":"sha256:a43109bbeabf7f445a56e9b053396c7d9ac4a488acb068775ba4395d6ef95288"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:SL447NJTJIU2DFYRQLIJYXFARC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Forget What's Sensitive, Remember What Matters: Token-Level Differential Privacy in Memory Sculpting for Continual Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Bihao Zhan, Hang Yan, Jie Zhou, Junsong Li, Liang He, Qianjun Pan, Qin Chen, Shilian Chen, Wen Wu, Xingjiao Wu, Xin Li, Yutao Yang","submitted_at":"2025-09-16T11:01:59Z","abstract_excerpt":"Continual Learning (CL) models, while adept at sequential knowledge acquisition, face significant and often overlooked privacy challenges due to accumulating diverse information. Traditional privacy methods, like a uniform Differential Privacy (DP) budget, indiscriminately protect all data, leading to substantial model utility degradation and hindering CL deployment in privacy-sensitive areas. To overcome this, we propose a privacy-enhanced continual learning (PeCL) framework that forgets what's sensitive and remembers what matters. Our approach first introduces a token-level dynamic Different"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.12958","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/2509.12958/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":"2026-05-25T02:01:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rXOU+EbL4mEI/qzPLNKmBGOFj3uyCwtZhpFCHXQKcK+fKtBU69cIiulU9hTr/jEknAia9B86UnGm0bgDAp9EBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T23:07:00.201234Z"},"content_sha256":"521c224fa296db2105316974cee80cc5331f8d398fb01fc109b4010abba3b2fa","schema_version":"1.0","event_id":"sha256:521c224fa296db2105316974cee80cc5331f8d398fb01fc109b4010abba3b2fa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SL447NJTJIU2DFYRQLIJYXFARC/bundle.json","state_url":"https://pith.science/pith/SL447NJTJIU2DFYRQLIJYXFARC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SL447NJTJIU2DFYRQLIJYXFARC/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":"2026-05-25T23:07:00Z","links":{"resolver":"https://pith.science/pith/SL447NJTJIU2DFYRQLIJYXFARC","bundle":"https://pith.science/pith/SL447NJTJIU2DFYRQLIJYXFARC/bundle.json","state":"https://pith.science/pith/SL447NJTJIU2DFYRQLIJYXFARC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SL447NJTJIU2DFYRQLIJYXFARC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SL447NJTJIU2DFYRQLIJYXFARC","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":"ae2b023409ca97433fa47292bc60518e90eb17efb2f6e908e4a7ecb555a38e91","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-09-16T11:01:59Z","title_canon_sha256":"5a673e03ca4beede9b5b02d43715e59652095c1cdf7a7e988b2018214a904aa5"},"schema_version":"1.0","source":{"id":"2509.12958","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.12958","created_at":"2026-05-25T02:01:07Z"},{"alias_kind":"arxiv_version","alias_value":"2509.12958v2","created_at":"2026-05-25T02:01:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.12958","created_at":"2026-05-25T02:01:07Z"},{"alias_kind":"pith_short_12","alias_value":"SL447NJTJIU2","created_at":"2026-05-25T02:01:07Z"},{"alias_kind":"pith_short_16","alias_value":"SL447NJTJIU2DFYR","created_at":"2026-05-25T02:01:07Z"},{"alias_kind":"pith_short_8","alias_value":"SL447NJT","created_at":"2026-05-25T02:01:07Z"}],"graph_snapshots":[{"event_id":"sha256:521c224fa296db2105316974cee80cc5331f8d398fb01fc109b4010abba3b2fa","target":"graph","created_at":"2026-05-25T02:01:07Z","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/2509.12958/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Continual Learning (CL) models, while adept at sequential knowledge acquisition, face significant and often overlooked privacy challenges due to accumulating diverse information. Traditional privacy methods, like a uniform Differential Privacy (DP) budget, indiscriminately protect all data, leading to substantial model utility degradation and hindering CL deployment in privacy-sensitive areas. To overcome this, we propose a privacy-enhanced continual learning (PeCL) framework that forgets what's sensitive and remembers what matters. Our approach first introduces a token-level dynamic Different","authors_text":"Bihao Zhan, Hang Yan, Jie Zhou, Junsong Li, Liang He, Qianjun Pan, Qin Chen, Shilian Chen, Wen Wu, Xingjiao Wu, Xin Li, Yutao Yang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-09-16T11:01:59Z","title":"Forget What's Sensitive, Remember What Matters: Token-Level Differential Privacy in Memory Sculpting for Continual Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.12958","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:a43109bbeabf7f445a56e9b053396c7d9ac4a488acb068775ba4395d6ef95288","target":"record","created_at":"2026-05-25T02:01:07Z","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":"ae2b023409ca97433fa47292bc60518e90eb17efb2f6e908e4a7ecb555a38e91","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-09-16T11:01:59Z","title_canon_sha256":"5a673e03ca4beede9b5b02d43715e59652095c1cdf7a7e988b2018214a904aa5"},"schema_version":"1.0","source":{"id":"2509.12958","kind":"arxiv","version":2}},"canonical_sha256":"92f9cfb5334a29a1971182d09c5ca088a718101108dd2d1e7630da6c8172d053","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"92f9cfb5334a29a1971182d09c5ca088a718101108dd2d1e7630da6c8172d053","first_computed_at":"2026-05-25T02:01:07.164300Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-25T02:01:07.164300Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8PZqrIekcyIH6adnujzq1Bi+YbjWKP2JUkz8dR7TbXHdynBDAAB9wDpiPQNe1HaTajsRf7gAMw0RsOx9ZwfCDA==","signature_status":"signed_v1","signed_at":"2026-05-25T02:01:07.165142Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.12958","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a43109bbeabf7f445a56e9b053396c7d9ac4a488acb068775ba4395d6ef95288","sha256:521c224fa296db2105316974cee80cc5331f8d398fb01fc109b4010abba3b2fa"],"state_sha256":"6f124621729437e43ea1835bfd2c330f0784e9b92d97fc7ecd17c15869c24b30"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BJ0BQHIPfgcgFItDcY1//SEYaHJ0V3BkoY91SbWqwbDHZs5rIInxTs0K2NiUNUF74LJ8H4SZ16pNvTes5WpyAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T23:07:00.205840Z","bundle_sha256":"2f34465eee494850918b7c704d0c8af7cd78b042c7a9209abdc1faeda76759ec"}}