{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:3KCWBGF4S3RVBRSJ7MBRXTPUIU","short_pith_number":"pith:3KCWBGF4","schema_version":"1.0","canonical_sha256":"da856098bc96e350c649fb031bcdf4452f77cdb2184f786dc55fb9f74f5de6fe","source":{"kind":"arxiv","id":"2606.12655","version":1},"attestation_state":"computed","paper":{"title":"Amnesia: A Stealthy Replay Attack on Continual Learning Dreams","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.CR","authors_text":"Ahmed Sharshar, Mohsen Guizani, Naveen Kumar Kummari","submitted_at":"2026-06-10T20:27:06Z","abstract_excerpt":"Continual learning (CL) models often use experience replay to reduce catastrophic forgetting, but their robustness to replay sampling interference remains underexplored. Existing CL attacks alter inputs or training pipelines (poisoning/backdoors) and rarely include explicit auditable constraints, limiting realism. Here, auditability means a monitor can verify compliance from sampler-visible telemetry - e.g., logged replay index/label statistics - by checking that the realized replay class histogram stays close to a nominal baseline and that replay rate is unchanged per batch and/or over a roll"},"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":"2606.12655","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2026-06-10T20:27:06Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"89cfeb953028d988ae143c362e4058af1326553ff0b8105acc3d65207f66c198","abstract_canon_sha256":"9b0b8819e5c6928761c9ab37e18e109aa2e5f3af61845b3c3f92275966c3b36d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-12T01:08:42.928017Z","signature_b64":"haf1twX9GHejHrn9k4Nbvqw+ix6dSacpTW00n8Ovnwod1LEQo1pw/olYOg9G1iPAtMBimRdyBXGufwOYVY3ODw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"da856098bc96e350c649fb031bcdf4452f77cdb2184f786dc55fb9f74f5de6fe","last_reissued_at":"2026-06-12T01:08:42.927097Z","signature_status":"signed_v1","first_computed_at":"2026-06-12T01:08:42.927097Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Amnesia: A Stealthy Replay Attack on Continual Learning Dreams","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.CR","authors_text":"Ahmed Sharshar, Mohsen Guizani, Naveen Kumar Kummari","submitted_at":"2026-06-10T20:27:06Z","abstract_excerpt":"Continual learning (CL) models often use experience replay to reduce catastrophic forgetting, but their robustness to replay sampling interference remains underexplored. Existing CL attacks alter inputs or training pipelines (poisoning/backdoors) and rarely include explicit auditable constraints, limiting realism. Here, auditability means a monitor can verify compliance from sampler-visible telemetry - e.g., logged replay index/label statistics - by checking that the realized replay class histogram stays close to a nominal baseline and that replay rate is unchanged per batch and/or over a roll"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.12655","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/2606.12655/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.12655","created_at":"2026-06-12T01:08:42.927245+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.12655v1","created_at":"2026-06-12T01:08:42.927245+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.12655","created_at":"2026-06-12T01:08:42.927245+00:00"},{"alias_kind":"pith_short_12","alias_value":"3KCWBGF4S3RV","created_at":"2026-06-12T01:08:42.927245+00:00"},{"alias_kind":"pith_short_16","alias_value":"3KCWBGF4S3RVBRSJ","created_at":"2026-06-12T01:08:42.927245+00:00"},{"alias_kind":"pith_short_8","alias_value":"3KCWBGF4","created_at":"2026-06-12T01:08:42.927245+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/3KCWBGF4S3RVBRSJ7MBRXTPUIU","json":"https://pith.science/pith/3KCWBGF4S3RVBRSJ7MBRXTPUIU.json","graph_json":"https://pith.science/api/pith-number/3KCWBGF4S3RVBRSJ7MBRXTPUIU/graph.json","events_json":"https://pith.science/api/pith-number/3KCWBGF4S3RVBRSJ7MBRXTPUIU/events.json","paper":"https://pith.science/paper/3KCWBGF4"},"agent_actions":{"view_html":"https://pith.science/pith/3KCWBGF4S3RVBRSJ7MBRXTPUIU","download_json":"https://pith.science/pith/3KCWBGF4S3RVBRSJ7MBRXTPUIU.json","view_paper":"https://pith.science/paper/3KCWBGF4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.12655&json=true","fetch_graph":"https://pith.science/api/pith-number/3KCWBGF4S3RVBRSJ7MBRXTPUIU/graph.json","fetch_events":"https://pith.science/api/pith-number/3KCWBGF4S3RVBRSJ7MBRXTPUIU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3KCWBGF4S3RVBRSJ7MBRXTPUIU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3KCWBGF4S3RVBRSJ7MBRXTPUIU/action/storage_attestation","attest_author":"https://pith.science/pith/3KCWBGF4S3RVBRSJ7MBRXTPUIU/action/author_attestation","sign_citation":"https://pith.science/pith/3KCWBGF4S3RVBRSJ7MBRXTPUIU/action/citation_signature","submit_replication":"https://pith.science/pith/3KCWBGF4S3RVBRSJ7MBRXTPUIU/action/replication_record"}},"created_at":"2026-06-12T01:08:42.927245+00:00","updated_at":"2026-06-12T01:08:42.927245+00:00"}