{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:I3AHSO3ZAPN45PQIE5YSFF6FTP","short_pith_number":"pith:I3AHSO3Z","schema_version":"1.0","canonical_sha256":"46c0793b7903dbcebe0827712297c59be18f22d8c10659e6b3cd130dc66fbe6b","source":{"kind":"arxiv","id":"2606.06494","version":1},"attestation_state":"computed","paper":{"title":"TailLoR: Protecting Principal Components in Parameter-Efficient Continual Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Alexandra Dragomir, Antonio Barbalau, Florin Brad, Ioana Pintilie, Marius Dragoi","submitted_at":"2026-06-04T17:59:55Z","abstract_excerpt":"Parameter-efficient finetuning methods based on spectral decomposition have enabled progress in Continual Learning. In this paper we introduce TailLoR, which utilizes the singular bases U and V of the pre-trained weights as a fixed reference frame to learn a low-rank update applied to the singular value matrix. A soft spectral penalty discourages updates aligned with dominant singular directions, reducing interference while routing fine-grained adaptation into the highly flexible, long-tail spectral coordinates."},"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":"2606.06494","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-04T17:59:55Z","cross_cats_sorted":[],"title_canon_sha256":"6837a522dd3634ec46e959be638ea03de470f509a9e6d4d94a290e6ec4d52155","abstract_canon_sha256":"953d72785466db1570c8556ca1c9236a505c3e4e6e905b41191cfc17b3b9d5da"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-05T01:15:47.168903Z","signature_b64":"kCijakTcXODMUXyVhoqYmsmf0mqUsVYlLlq3axck4vR+d3MZvdaKpJ9ewaS9oED0uFC5Qlwn2BKH3nmDzeEVBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"46c0793b7903dbcebe0827712297c59be18f22d8c10659e6b3cd130dc66fbe6b","last_reissued_at":"2026-06-05T01:15:47.168387Z","signature_status":"signed_v1","first_computed_at":"2026-06-05T01:15:47.168387Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"TailLoR: Protecting Principal Components in Parameter-Efficient Continual Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Alexandra Dragomir, Antonio Barbalau, Florin Brad, Ioana Pintilie, Marius Dragoi","submitted_at":"2026-06-04T17:59:55Z","abstract_excerpt":"Parameter-efficient finetuning methods based on spectral decomposition have enabled progress in Continual Learning. In this paper we introduce TailLoR, which utilizes the singular bases U and V of the pre-trained weights as a fixed reference frame to learn a low-rank update applied to the singular value matrix. A soft spectral penalty discourages updates aligned with dominant singular directions, reducing interference while routing fine-grained adaptation into the highly flexible, long-tail spectral coordinates."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.06494","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/2606.06494/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":"2606.06494","created_at":"2026-06-05T01:15:47.168452+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.06494v1","created_at":"2026-06-05T01:15:47.168452+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.06494","created_at":"2026-06-05T01:15:47.168452+00:00"},{"alias_kind":"pith_short_12","alias_value":"I3AHSO3ZAPN4","created_at":"2026-06-05T01:15:47.168452+00:00"},{"alias_kind":"pith_short_16","alias_value":"I3AHSO3ZAPN45PQI","created_at":"2026-06-05T01:15:47.168452+00:00"},{"alias_kind":"pith_short_8","alias_value":"I3AHSO3Z","created_at":"2026-06-05T01:15:47.168452+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/I3AHSO3ZAPN45PQIE5YSFF6FTP","json":"https://pith.science/pith/I3AHSO3ZAPN45PQIE5YSFF6FTP.json","graph_json":"https://pith.science/api/pith-number/I3AHSO3ZAPN45PQIE5YSFF6FTP/graph.json","events_json":"https://pith.science/api/pith-number/I3AHSO3ZAPN45PQIE5YSFF6FTP/events.json","paper":"https://pith.science/paper/I3AHSO3Z"},"agent_actions":{"view_html":"https://pith.science/pith/I3AHSO3ZAPN45PQIE5YSFF6FTP","download_json":"https://pith.science/pith/I3AHSO3ZAPN45PQIE5YSFF6FTP.json","view_paper":"https://pith.science/paper/I3AHSO3Z","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.06494&json=true","fetch_graph":"https://pith.science/api/pith-number/I3AHSO3ZAPN45PQIE5YSFF6FTP/graph.json","fetch_events":"https://pith.science/api/pith-number/I3AHSO3ZAPN45PQIE5YSFF6FTP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/I3AHSO3ZAPN45PQIE5YSFF6FTP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/I3AHSO3ZAPN45PQIE5YSFF6FTP/action/storage_attestation","attest_author":"https://pith.science/pith/I3AHSO3ZAPN45PQIE5YSFF6FTP/action/author_attestation","sign_citation":"https://pith.science/pith/I3AHSO3ZAPN45PQIE5YSFF6FTP/action/citation_signature","submit_replication":"https://pith.science/pith/I3AHSO3ZAPN45PQIE5YSFF6FTP/action/replication_record"}},"created_at":"2026-06-05T01:15:47.168452+00:00","updated_at":"2026-06-05T01:15:47.168452+00:00"}