{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ZBSFJJDARVEVYOI6GUWSMC6BKD","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":"fa4d73a67a0fe8523bdbb9c119a00f8e68fb1a77301104ff3a891bbb60dc09ac","cross_cats_sorted":["cs.CL","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-01T00:29:13Z","title_canon_sha256":"038633df893c0306f576a0e2be01d5fc83ad2504e6da7bf4dc63195b287f3da3"},"schema_version":"1.0","source":{"id":"2508.00230","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.00230","created_at":"2026-07-05T11:46:51Z"},{"alias_kind":"arxiv_version","alias_value":"2508.00230v1","created_at":"2026-07-05T11:46:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.00230","created_at":"2026-07-05T11:46:51Z"},{"alias_kind":"pith_short_12","alias_value":"ZBSFJJDARVEV","created_at":"2026-07-05T11:46:51Z"},{"alias_kind":"pith_short_16","alias_value":"ZBSFJJDARVEVYOI6","created_at":"2026-07-05T11:46:51Z"},{"alias_kind":"pith_short_8","alias_value":"ZBSFJJDA","created_at":"2026-07-05T11:46:51Z"}],"graph_snapshots":[{"event_id":"sha256:532c687367930785fa82f0f08bfc0531d9b7471ed67ff639f5fa813a750b73ec","target":"graph","created_at":"2026-07-05T11:46:51Z","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/2508.00230/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Parameter-efficient fine-tuning (PEFT) has become a standard approach for adapting large pre-trained models. Amongst PEFT methods, low-rank adaptation (LoRA) has achieved notable success. However, recent studies have highlighted its limitations compared against full-rank alternatives, particularly when applied to multimodal and large language models. In this work, we present a quantitative comparison amongst full-rank and low-rank PEFT methods using a synthetic matrix approximation benchmark with controlled spectral properties. Our results confirm that LoRA struggles to approximate matrices wi","authors_text":"Anton van den Hengel, Ehsan Abbasnejad, Frederic Z. Zhang, Hemanth Saratchandran, Paul Albert","cross_cats":["cs.CL","cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-01T00:29:13Z","title":"Towards Higher Effective Rank in Parameter-efficient Fine-tuning using Khatri--Rao Product"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.00230","kind":"arxiv","version":1},"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":"sha256:543592410c815b8fca4f53a7d4b6bab7535702b0729e5bf89eae9fe4e0a985ae","target":"record","created_at":"2026-07-05T11:46:51Z","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":"fa4d73a67a0fe8523bdbb9c119a00f8e68fb1a77301104ff3a891bbb60dc09ac","cross_cats_sorted":["cs.CL","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-01T00:29:13Z","title_canon_sha256":"038633df893c0306f576a0e2be01d5fc83ad2504e6da7bf4dc63195b287f3da3"},"schema_version":"1.0","source":{"id":"2508.00230","kind":"arxiv","version":1}},"canonical_sha256":"c86454a4608d495c391e352d260bc150d4a8cbc732a046627b45256f270ebec6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c86454a4608d495c391e352d260bc150d4a8cbc732a046627b45256f270ebec6","first_computed_at":"2026-07-05T11:46:51.601351Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:46:51.601351Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mdIYfDSCdxNGBS2CY7/yUUhlO2JBxJgg4clvEbg3VwE/o4GrBWgiWgLIAx1fNCosf9gktmMRTE4E5uYnsvIRAw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:46:51.601741Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.00230","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:543592410c815b8fca4f53a7d4b6bab7535702b0729e5bf89eae9fe4e0a985ae","sha256:532c687367930785fa82f0f08bfc0531d9b7471ed67ff639f5fa813a750b73ec"],"state_sha256":"5b6888862bfe79010f52ccdf423e3c644144f8a41fe95c166db7040e673fab36"}