{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:GPE24OLRZT3Y5CGSOC7IWMIGBC","short_pith_number":"pith:GPE24OLR","schema_version":"1.0","canonical_sha256":"33c9ae3971ccf78e88d270be8b310608ad8adc92f1f3a44774f8b57aa8f6bf5a","source":{"kind":"arxiv","id":"2506.16787","version":1},"attestation_state":"computed","paper":{"title":"Revisiting LoRA through the Lens of Parameter Redundancy: Spectral Encoding Helps","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Aochuan Chen, Fugee Tsung, Jia Li, Jiashun Cheng, Nuo Chen, Yuhan Li, Ziqi Gao","submitted_at":"2025-06-20T07:09:05Z","abstract_excerpt":"Low-Rank Adaptation (LoRA) has emerged as a prominent technique for fine-tuning large foundation models. Despite its successes, the substantial parameter redundancy, which limits the capacity and efficiency of LoRA, has been recognized as a bottleneck. In this work, we systematically investigate the impact of redundancy in fine-tuning LoRA and reveal that reducing density redundancy does not degrade expressiveness. Based on this insight, we introduce \\underline{S}pectral-\\underline{e}ncoding \\underline{L}ow-\\underline{R}ank \\underline{A}daptation (SeLoRA), which harnesses the robust expressive"},"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":"2506.16787","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-20T07:09:05Z","cross_cats_sorted":[],"title_canon_sha256":"397144441e6fbd9aededd5954a1b658beca2fae29a206fa64ce2768deaaa8cb9","abstract_canon_sha256":"732e1660e75bd02862faeba27e8edd48c03c47c80c89c88b5c7fd1b49fb03709"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:24:43.030260Z","signature_b64":"wjjDuxcojqPHQ2zFH23SFBsqSqDlF7/+9/XT7Of6BJt+9TqL0wjNxbla0DmlBI3LpJCoLqGtViRIwZj2Ol7LBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"33c9ae3971ccf78e88d270be8b310608ad8adc92f1f3a44774f8b57aa8f6bf5a","last_reissued_at":"2026-07-05T11:24:43.029854Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:24:43.029854Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Revisiting LoRA through the Lens of Parameter Redundancy: Spectral Encoding Helps","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Aochuan Chen, Fugee Tsung, Jia Li, Jiashun Cheng, Nuo Chen, Yuhan Li, Ziqi Gao","submitted_at":"2025-06-20T07:09:05Z","abstract_excerpt":"Low-Rank Adaptation (LoRA) has emerged as a prominent technique for fine-tuning large foundation models. Despite its successes, the substantial parameter redundancy, which limits the capacity and efficiency of LoRA, has been recognized as a bottleneck. In this work, we systematically investigate the impact of redundancy in fine-tuning LoRA and reveal that reducing density redundancy does not degrade expressiveness. Based on this insight, we introduce \\underline{S}pectral-\\underline{e}ncoding \\underline{L}ow-\\underline{R}ank \\underline{A}daptation (SeLoRA), which harnesses the robust expressive"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.16787","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/2506.16787/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":"2506.16787","created_at":"2026-07-05T11:24:43.029907+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.16787v1","created_at":"2026-07-05T11:24:43.029907+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.16787","created_at":"2026-07-05T11:24:43.029907+00:00"},{"alias_kind":"pith_short_12","alias_value":"GPE24OLRZT3Y","created_at":"2026-07-05T11:24:43.029907+00:00"},{"alias_kind":"pith_short_16","alias_value":"GPE24OLRZT3Y5CGS","created_at":"2026-07-05T11:24:43.029907+00:00"},{"alias_kind":"pith_short_8","alias_value":"GPE24OLR","created_at":"2026-07-05T11:24:43.029907+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/GPE24OLRZT3Y5CGSOC7IWMIGBC","json":"https://pith.science/pith/GPE24OLRZT3Y5CGSOC7IWMIGBC.json","graph_json":"https://pith.science/api/pith-number/GPE24OLRZT3Y5CGSOC7IWMIGBC/graph.json","events_json":"https://pith.science/api/pith-number/GPE24OLRZT3Y5CGSOC7IWMIGBC/events.json","paper":"https://pith.science/paper/GPE24OLR"},"agent_actions":{"view_html":"https://pith.science/pith/GPE24OLRZT3Y5CGSOC7IWMIGBC","download_json":"https://pith.science/pith/GPE24OLRZT3Y5CGSOC7IWMIGBC.json","view_paper":"https://pith.science/paper/GPE24OLR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.16787&json=true","fetch_graph":"https://pith.science/api/pith-number/GPE24OLRZT3Y5CGSOC7IWMIGBC/graph.json","fetch_events":"https://pith.science/api/pith-number/GPE24OLRZT3Y5CGSOC7IWMIGBC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GPE24OLRZT3Y5CGSOC7IWMIGBC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GPE24OLRZT3Y5CGSOC7IWMIGBC/action/storage_attestation","attest_author":"https://pith.science/pith/GPE24OLRZT3Y5CGSOC7IWMIGBC/action/author_attestation","sign_citation":"https://pith.science/pith/GPE24OLRZT3Y5CGSOC7IWMIGBC/action/citation_signature","submit_replication":"https://pith.science/pith/GPE24OLRZT3Y5CGSOC7IWMIGBC/action/replication_record"}},"created_at":"2026-07-05T11:24:43.029907+00:00","updated_at":"2026-07-05T11:24:43.029907+00:00"}