{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GW5ZX2L2RZLCRJYPVNTVPDDMNQ","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":"ef47bdd88504c7e2400e5f06d17c9e295d52ebf463990da03616c21b3a40dd4b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-15T15:43:52Z","title_canon_sha256":"0341c12da522a2093ea3036b5054fdff8ee955435a2d7915ea79d149e254e4c8"},"schema_version":"1.0","source":{"id":"2404.09872","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.09872","created_at":"2026-07-05T08:57:02Z"},{"alias_kind":"arxiv_version","alias_value":"2404.09872v2","created_at":"2026-07-05T08:57:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.09872","created_at":"2026-07-05T08:57:02Z"},{"alias_kind":"pith_short_12","alias_value":"GW5ZX2L2RZLC","created_at":"2026-07-05T08:57:02Z"},{"alias_kind":"pith_short_16","alias_value":"GW5ZX2L2RZLCRJYP","created_at":"2026-07-05T08:57:02Z"},{"alias_kind":"pith_short_8","alias_value":"GW5ZX2L2","created_at":"2026-07-05T08:57:02Z"}],"graph_snapshots":[{"event_id":"sha256:31ac53d44fec41d03896439ed8705bd24d647573e337eb010a163be48049d263","target":"graph","created_at":"2026-07-05T08:57:02Z","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/2404.09872/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Pre-trained large-scale vision-language models (VLMs) have acquired profound understanding of general visual concepts. Recent advancements in efficient transfer learning (ETL) have shown remarkable success in fine-tuning VLMs within the scenario of limited data, introducing only a few parameters to harness task-specific insights from VLMs. Despite significant progress, current leading ETL methods tend to overfit the narrow distributions of base classes seen during training and encounter two primary challenges: (i) only utilizing uni-modal information to modeling task-specific knowledge; and (i","authors_text":"Haoxing Chen, Huijia Zhu, Jun Lan, Weiqiang Wang, Yan Hong, Yaohui Li, Zhangxuan Gu, Zhuoer Xu, Zizheng Huang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-15T15:43:52Z","title":"Conditional Prototype Rectification Prompt Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.09872","kind":"arxiv","version":2},"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":"sha256:73aca26d4064f29eef19a12216a44982527559e029aef5019c62b148753bdcd3","target":"record","created_at":"2026-07-05T08:57:02Z","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":"ef47bdd88504c7e2400e5f06d17c9e295d52ebf463990da03616c21b3a40dd4b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-15T15:43:52Z","title_canon_sha256":"0341c12da522a2093ea3036b5054fdff8ee955435a2d7915ea79d149e254e4c8"},"schema_version":"1.0","source":{"id":"2404.09872","kind":"arxiv","version":2}},"canonical_sha256":"35bb9be97a8e5628a70fab67578c6c6c0f9dc3d2f284376587defd89d1b18598","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"35bb9be97a8e5628a70fab67578c6c6c0f9dc3d2f284376587defd89d1b18598","first_computed_at":"2026-07-05T08:57:02.323772Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:57:02.323772Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dnNjzqupVzcerpgplaUbf0SWMThKWB641GhSH/0Ne0Lu26STWPl+1wlrSxIBiIoceiWa/EH6SJ09VYWalvG8DA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:57:02.324173Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.09872","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:73aca26d4064f29eef19a12216a44982527559e029aef5019c62b148753bdcd3","sha256:31ac53d44fec41d03896439ed8705bd24d647573e337eb010a163be48049d263"],"state_sha256":"8b8b2565b25358c6cd3571c462c29cbc77d12f2b7dc39a747a9b109b7f6641c0"}