{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:PNK53AJ2ZQJBLCJSXFGYXM364W","short_pith_number":"pith:PNK53AJ2","canonical_record":{"source":{"id":"2311.16494","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-27T10:34:44Z","cross_cats_sorted":[],"title_canon_sha256":"7a363b35493d305066fc9e964e9fbc9da8064c78574b8cd1de13fefccbd820ab","abstract_canon_sha256":"782335ac8ad1f375b037f81591fc40f41895938f0bf2d66c20e9e337f6f9e882"},"schema_version":"1.0"},"canonical_sha256":"7b55dd813acc12158932b94d8bb37ee5a5e546681b191d47d6686b58dc02d40c","source":{"kind":"arxiv","id":"2311.16494","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.16494","created_at":"2026-07-05T07:55:26Z"},{"alias_kind":"arxiv_version","alias_value":"2311.16494v2","created_at":"2026-07-05T07:55:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.16494","created_at":"2026-07-05T07:55:26Z"},{"alias_kind":"pith_short_12","alias_value":"PNK53AJ2ZQJB","created_at":"2026-07-05T07:55:26Z"},{"alias_kind":"pith_short_16","alias_value":"PNK53AJ2ZQJBLCJS","created_at":"2026-07-05T07:55:26Z"},{"alias_kind":"pith_short_8","alias_value":"PNK53AJ2","created_at":"2026-07-05T07:55:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:PNK53AJ2ZQJBLCJSXFGYXM364W","target":"record","payload":{"canonical_record":{"source":{"id":"2311.16494","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-27T10:34:44Z","cross_cats_sorted":[],"title_canon_sha256":"7a363b35493d305066fc9e964e9fbc9da8064c78574b8cd1de13fefccbd820ab","abstract_canon_sha256":"782335ac8ad1f375b037f81591fc40f41895938f0bf2d66c20e9e337f6f9e882"},"schema_version":"1.0"},"canonical_sha256":"7b55dd813acc12158932b94d8bb37ee5a5e546681b191d47d6686b58dc02d40c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:55:26.708492Z","signature_b64":"PucZExZf5w90HGkxEpALhzVrl2BimmLsyuxeAaTIIbrYl/9qr2keowOibB5e1tjXrhkusV/WoEyzmi/ndEqrBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7b55dd813acc12158932b94d8bb37ee5a5e546681b191d47d6686b58dc02d40c","last_reissued_at":"2026-07-05T07:55:26.708021Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:55:26.708021Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.16494","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:55:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Oa0AnJXK8AJg4tPF1q9SAGnCetdrfNYbX+9mA3eqnWL79kHo8G4PXbJD+XNTKtzrNFv/JUsia6XxLvSyw8oKDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T18:18:20.935941Z"},"content_sha256":"9f481ca237ad1b314612319130dba60815549f3d988d8eaf4c2f6cc713b7ff6a","schema_version":"1.0","event_id":"sha256:9f481ca237ad1b314612319130dba60815549f3d988d8eaf4c2f6cc713b7ff6a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:PNK53AJ2ZQJBLCJSXFGYXM364W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ArGue: Attribute-Guided Prompt Tuning for Vision-Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jing Zhang, Shu Zou, Xinyu Tian, Zhaoyuan Yang","submitted_at":"2023-11-27T10:34:44Z","abstract_excerpt":"Although soft prompt tuning is effective in efficiently adapting Vision-Language (V&L) models for downstream tasks, it shows limitations in dealing with distribution shifts. We address this issue with Attribute-Guided Prompt Tuning (ArGue), making three key contributions. 1) In contrast to the conventional approach of directly appending soft prompts preceding class names, we align the model with primitive visual attributes generated by Large Language Models (LLMs). We posit that a model's ability to express high confidence in these attributes signifies its capacity to discern the correct class"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.16494","kind":"arxiv","version":2},"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/2311.16494/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:55:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DGNzRhR6IapWMNVbLHWcKDUkZt0S4rDRdDl7rcTZ+p7dXwls4NxUgfpzijfMQqLlpSEhWz3ipVVY9hWJLj2bAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T18:18:20.936506Z"},"content_sha256":"33d4d4b5b7220d8f25a10e2429ff6245cd886e8b3167c1506c89e7c4f988c678","schema_version":"1.0","event_id":"sha256:33d4d4b5b7220d8f25a10e2429ff6245cd886e8b3167c1506c89e7c4f988c678"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PNK53AJ2ZQJBLCJSXFGYXM364W/bundle.json","state_url":"https://pith.science/pith/PNK53AJ2ZQJBLCJSXFGYXM364W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PNK53AJ2ZQJBLCJSXFGYXM364W/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-21T18:18:20Z","links":{"resolver":"https://pith.science/pith/PNK53AJ2ZQJBLCJSXFGYXM364W","bundle":"https://pith.science/pith/PNK53AJ2ZQJBLCJSXFGYXM364W/bundle.json","state":"https://pith.science/pith/PNK53AJ2ZQJBLCJSXFGYXM364W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PNK53AJ2ZQJBLCJSXFGYXM364W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:PNK53AJ2ZQJBLCJSXFGYXM364W","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":"782335ac8ad1f375b037f81591fc40f41895938f0bf2d66c20e9e337f6f9e882","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-27T10:34:44Z","title_canon_sha256":"7a363b35493d305066fc9e964e9fbc9da8064c78574b8cd1de13fefccbd820ab"},"schema_version":"1.0","source":{"id":"2311.16494","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.16494","created_at":"2026-07-05T07:55:26Z"},{"alias_kind":"arxiv_version","alias_value":"2311.16494v2","created_at":"2026-07-05T07:55:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.16494","created_at":"2026-07-05T07:55:26Z"},{"alias_kind":"pith_short_12","alias_value":"PNK53AJ2ZQJB","created_at":"2026-07-05T07:55:26Z"},{"alias_kind":"pith_short_16","alias_value":"PNK53AJ2ZQJBLCJS","created_at":"2026-07-05T07:55:26Z"},{"alias_kind":"pith_short_8","alias_value":"PNK53AJ2","created_at":"2026-07-05T07:55:26Z"}],"graph_snapshots":[{"event_id":"sha256:33d4d4b5b7220d8f25a10e2429ff6245cd886e8b3167c1506c89e7c4f988c678","target":"graph","created_at":"2026-07-05T07:55:26Z","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/2311.16494/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Although soft prompt tuning is effective in efficiently adapting Vision-Language (V&L) models for downstream tasks, it shows limitations in dealing with distribution shifts. We address this issue with Attribute-Guided Prompt Tuning (ArGue), making three key contributions. 1) In contrast to the conventional approach of directly appending soft prompts preceding class names, we align the model with primitive visual attributes generated by Large Language Models (LLMs). We posit that a model's ability to express high confidence in these attributes signifies its capacity to discern the correct class","authors_text":"Jing Zhang, Shu Zou, Xinyu Tian, Zhaoyuan Yang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-27T10:34:44Z","title":"ArGue: Attribute-Guided Prompt Tuning for Vision-Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.16494","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":"sha256:9f481ca237ad1b314612319130dba60815549f3d988d8eaf4c2f6cc713b7ff6a","target":"record","created_at":"2026-07-05T07:55:26Z","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":"782335ac8ad1f375b037f81591fc40f41895938f0bf2d66c20e9e337f6f9e882","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-27T10:34:44Z","title_canon_sha256":"7a363b35493d305066fc9e964e9fbc9da8064c78574b8cd1de13fefccbd820ab"},"schema_version":"1.0","source":{"id":"2311.16494","kind":"arxiv","version":2}},"canonical_sha256":"7b55dd813acc12158932b94d8bb37ee5a5e546681b191d47d6686b58dc02d40c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7b55dd813acc12158932b94d8bb37ee5a5e546681b191d47d6686b58dc02d40c","first_computed_at":"2026-07-05T07:55:26.708021Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:55:26.708021Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PucZExZf5w90HGkxEpALhzVrl2BimmLsyuxeAaTIIbrYl/9qr2keowOibB5e1tjXrhkusV/WoEyzmi/ndEqrBg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:55:26.708492Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.16494","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9f481ca237ad1b314612319130dba60815549f3d988d8eaf4c2f6cc713b7ff6a","sha256:33d4d4b5b7220d8f25a10e2429ff6245cd886e8b3167c1506c89e7c4f988c678"],"state_sha256":"7a20bfd20e23c5b1c285b4bbb813d4ac5697177ffeee9b84d23bf2b30a6c9171"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B5pujH2uQ5VVhffLsHmOHGzCLw0XYr/B7KxTJsPHUQkIUv+i7zl4YsAKXhKgoaVY1yyJWCqwV9UPTBEW5G2WAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T18:18:20.940188Z","bundle_sha256":"ee7e3f94f9b305cd992ef039da0e4f8846872b96b5d70af58c7c3b92009c537f"}}