{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:H65MOXJHLPYOZ7T2UIXCFEOKTL","short_pith_number":"pith:H65MOXJH","schema_version":"1.0","canonical_sha256":"3fbac75d275bf0ecfe7aa22e2291ca9ae7706ead9d010da2568591bd2611a84d","source":{"kind":"arxiv","id":"2605.17590","version":1},"attestation_state":"computed","paper":{"title":"Form and Function: Machine Unlearning as a Problem of Misaligned States","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.LG","authors_text":"Kennon Stewart","submitted_at":"2026-05-17T18:34:14Z","abstract_excerpt":"We formulate machine unlearning for online L-BFGS as a counterfactual state-alignment problem. Given an actual event stream and a deletion-edited counterfactual stream, the target of unlearning is the optimizer state that would have arisen had the deleted samples never been processed. We introduce state-aware metrics that separately measure parameter error, memory-operator error, combined state error, and update-direction error. The memory metric compares the inverse-Hessian actions induced by the o-L-BFGS memory, rather than treating curvature pairs as of finite influence. Under convexity ass"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2605.17590","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-17T18:34:14Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"681c7d925833ecc1ed415809ab7c618eafb1f3851e8922d47567bfc73113d4c8","abstract_canon_sha256":"3f82047f8d5cde864ddff8a9f323a0f083b0409698c3e64030bc181a7d9bc138"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:04:47.529972Z","signature_b64":"zqoE3sM/jfXLDeRmAirckd7D2wbTQuEaPRDZ9bDxCzw1lmNdBPiOUn10OAw2FXxYHCTazmzCRbXNSBPVcTuFBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3fbac75d275bf0ecfe7aa22e2291ca9ae7706ead9d010da2568591bd2611a84d","last_reissued_at":"2026-05-20T00:04:47.529171Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:04:47.529171Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Form and Function: Machine Unlearning as a Problem of Misaligned States","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.LG","authors_text":"Kennon Stewart","submitted_at":"2026-05-17T18:34:14Z","abstract_excerpt":"We formulate machine unlearning for online L-BFGS as a counterfactual state-alignment problem. Given an actual event stream and a deletion-edited counterfactual stream, the target of unlearning is the optimizer state that would have arisen had the deleted samples never been processed. We introduce state-aware metrics that separately measure parameter error, memory-operator error, combined state error, and update-direction error. The memory metric compares the inverse-Hessian actions induced by the o-L-BFGS memory, rather than treating curvature pairs as of finite influence. Under convexity ass"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.17590","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/2605.17590/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-19T21:33:23.583856Z","status":"skipped","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T21:21:57.512912Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"9bc88ac5b847cee002cbfda7e66ce6bfc964c5a30a8a3dc500c5fb7d5cd08310"},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.17590","created_at":"2026-05-20T00:04:47.529284+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.17590v1","created_at":"2026-05-20T00:04:47.529284+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17590","created_at":"2026-05-20T00:04:47.529284+00:00"},{"alias_kind":"pith_short_12","alias_value":"H65MOXJHLPYO","created_at":"2026-05-20T00:04:47.529284+00:00"},{"alias_kind":"pith_short_16","alias_value":"H65MOXJHLPYOZ7T2","created_at":"2026-05-20T00:04:47.529284+00:00"},{"alias_kind":"pith_short_8","alias_value":"H65MOXJH","created_at":"2026-05-20T00:04:47.529284+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/H65MOXJHLPYOZ7T2UIXCFEOKTL","json":"https://pith.science/pith/H65MOXJHLPYOZ7T2UIXCFEOKTL.json","graph_json":"https://pith.science/api/pith-number/H65MOXJHLPYOZ7T2UIXCFEOKTL/graph.json","events_json":"https://pith.science/api/pith-number/H65MOXJHLPYOZ7T2UIXCFEOKTL/events.json","paper":"https://pith.science/paper/H65MOXJH"},"agent_actions":{"view_html":"https://pith.science/pith/H65MOXJHLPYOZ7T2UIXCFEOKTL","download_json":"https://pith.science/pith/H65MOXJHLPYOZ7T2UIXCFEOKTL.json","view_paper":"https://pith.science/paper/H65MOXJH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.17590&json=true","fetch_graph":"https://pith.science/api/pith-number/H65MOXJHLPYOZ7T2UIXCFEOKTL/graph.json","fetch_events":"https://pith.science/api/pith-number/H65MOXJHLPYOZ7T2UIXCFEOKTL/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/H65MOXJHLPYOZ7T2UIXCFEOKTL/action/timestamp_anchor","attest_storage":"https://pith.science/pith/H65MOXJHLPYOZ7T2UIXCFEOKTL/action/storage_attestation","attest_author":"https://pith.science/pith/H65MOXJHLPYOZ7T2UIXCFEOKTL/action/author_attestation","sign_citation":"https://pith.science/pith/H65MOXJHLPYOZ7T2UIXCFEOKTL/action/citation_signature","submit_replication":"https://pith.science/pith/H65MOXJHLPYOZ7T2UIXCFEOKTL/action/replication_record"}},"created_at":"2026-05-20T00:04:47.529284+00:00","updated_at":"2026-05-20T00:04:47.529284+00:00"}