{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:7EDGGDV7ZF7MWPHRULMIFPMDHC","short_pith_number":"pith:7EDGGDV7","canonical_record":{"source":{"id":"2402.04655","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-07T08:42:48Z","cross_cats_sorted":[],"title_canon_sha256":"97a24c593545837e838b840821f82912291dc09658837ff7f05f1f4fb66481a5","abstract_canon_sha256":"04335c94f8d5c95d7358a2feca93b6d43332d08ddaf87f8358b025da386b68ae"},"schema_version":"1.0"},"canonical_sha256":"f906630ebfc97ecb3cf1a2d882bd83389a4b26063b245ed2dabde1719af305e4","source":{"kind":"arxiv","id":"2402.04655","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.04655","created_at":"2026-07-05T08:31:48Z"},{"alias_kind":"arxiv_version","alias_value":"2402.04655v4","created_at":"2026-07-05T08:31:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.04655","created_at":"2026-07-05T08:31:48Z"},{"alias_kind":"pith_short_12","alias_value":"7EDGGDV7ZF7M","created_at":"2026-07-05T08:31:48Z"},{"alias_kind":"pith_short_16","alias_value":"7EDGGDV7ZF7MWPHR","created_at":"2026-07-05T08:31:48Z"},{"alias_kind":"pith_short_8","alias_value":"7EDGGDV7","created_at":"2026-07-05T08:31:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:7EDGGDV7ZF7MWPHRULMIFPMDHC","target":"record","payload":{"canonical_record":{"source":{"id":"2402.04655","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-07T08:42:48Z","cross_cats_sorted":[],"title_canon_sha256":"97a24c593545837e838b840821f82912291dc09658837ff7f05f1f4fb66481a5","abstract_canon_sha256":"04335c94f8d5c95d7358a2feca93b6d43332d08ddaf87f8358b025da386b68ae"},"schema_version":"1.0"},"canonical_sha256":"f906630ebfc97ecb3cf1a2d882bd83389a4b26063b245ed2dabde1719af305e4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:31:48.253393Z","signature_b64":"6mwAGD1R7WW7sPKoiWzXyUHEW3qJryqbkf0KqzZtPP1KU0qVqF/hVbIrtvxC6mE3yo3hL61lWYqpr1wUy4laBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f906630ebfc97ecb3cf1a2d882bd83389a4b26063b245ed2dabde1719af305e4","last_reissued_at":"2026-07-05T08:31:48.252896Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:31:48.252896Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.04655","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:31:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WXaBQyo5ssyoARkNE3BEqI84oi5sDIDeZj89QgzobEMZZiTF94WK4dd/V11NoIx6D3Sk3B0zcToKpdVsbBgrDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T17:06:28.478003Z"},"content_sha256":"d0fb9c0dfceca8900f0bb6e7c32bb6d904e1c56b3921ea7d5b30555e8a4f46fe","schema_version":"1.0","event_id":"sha256:d0fb9c0dfceca8900f0bb6e7c32bb6d904e1c56b3921ea7d5b30555e8a4f46fe"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:7EDGGDV7ZF7MWPHRULMIFPMDHC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Open-Vocabulary Calibration for Fine-tuned CLIP","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Bob Zhang, Guoqing Wang, Hongxin Wei, Jindong Wang, Kaiyang Zhou, Shuoyuan Wang","submitted_at":"2024-02-07T08:42:48Z","abstract_excerpt":"Vision-language models (VLMs) have emerged as formidable tools, showing their strong capability in handling various open-vocabulary tasks in image recognition, text-driven visual content generation, and visual chatbots, to name a few. In recent years, considerable efforts and resources have been devoted to adaptation methods for improving downstream performance of VLMs, particularly on parameter-efficient fine-tuning methods like prompt learning. However, a crucial aspect that has been largely overlooked is the confidence calibration problem in fine-tuned VLMs, which could greatly reduce relia"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.04655","kind":"arxiv","version":4},"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/2402.04655/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":"2026-07-05T08:31:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/voA6XncoZ/qMJWyVcC2N1gO9YKSR3CYGtkF/hsSgfp1FO0mZinCt26tnviwsSz5NjFP1UY/2VOlC9S/bUwbDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T17:06:28.478550Z"},"content_sha256":"eb0dd1207c4ef2d0d7223866a141eb30d63164ead123bd39ad4315bbc7b9091c","schema_version":"1.0","event_id":"sha256:eb0dd1207c4ef2d0d7223866a141eb30d63164ead123bd39ad4315bbc7b9091c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7EDGGDV7ZF7MWPHRULMIFPMDHC/bundle.json","state_url":"https://pith.science/pith/7EDGGDV7ZF7MWPHRULMIFPMDHC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7EDGGDV7ZF7MWPHRULMIFPMDHC/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":"2026-08-07T17:06:28Z","links":{"resolver":"https://pith.science/pith/7EDGGDV7ZF7MWPHRULMIFPMDHC","bundle":"https://pith.science/pith/7EDGGDV7ZF7MWPHRULMIFPMDHC/bundle.json","state":"https://pith.science/pith/7EDGGDV7ZF7MWPHRULMIFPMDHC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7EDGGDV7ZF7MWPHRULMIFPMDHC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:7EDGGDV7ZF7MWPHRULMIFPMDHC","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":"04335c94f8d5c95d7358a2feca93b6d43332d08ddaf87f8358b025da386b68ae","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-07T08:42:48Z","title_canon_sha256":"97a24c593545837e838b840821f82912291dc09658837ff7f05f1f4fb66481a5"},"schema_version":"1.0","source":{"id":"2402.04655","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.04655","created_at":"2026-07-05T08:31:48Z"},{"alias_kind":"arxiv_version","alias_value":"2402.04655v4","created_at":"2026-07-05T08:31:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.04655","created_at":"2026-07-05T08:31:48Z"},{"alias_kind":"pith_short_12","alias_value":"7EDGGDV7ZF7M","created_at":"2026-07-05T08:31:48Z"},{"alias_kind":"pith_short_16","alias_value":"7EDGGDV7ZF7MWPHR","created_at":"2026-07-05T08:31:48Z"},{"alias_kind":"pith_short_8","alias_value":"7EDGGDV7","created_at":"2026-07-05T08:31:48Z"}],"graph_snapshots":[{"event_id":"sha256:eb0dd1207c4ef2d0d7223866a141eb30d63164ead123bd39ad4315bbc7b9091c","target":"graph","created_at":"2026-07-05T08:31:48Z","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/2402.04655/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vision-language models (VLMs) have emerged as formidable tools, showing their strong capability in handling various open-vocabulary tasks in image recognition, text-driven visual content generation, and visual chatbots, to name a few. In recent years, considerable efforts and resources have been devoted to adaptation methods for improving downstream performance of VLMs, particularly on parameter-efficient fine-tuning methods like prompt learning. However, a crucial aspect that has been largely overlooked is the confidence calibration problem in fine-tuned VLMs, which could greatly reduce relia","authors_text":"Bob Zhang, Guoqing Wang, Hongxin Wei, Jindong Wang, Kaiyang Zhou, Shuoyuan Wang","cross_cats":[],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-07T08:42:48Z","title":"Open-Vocabulary Calibration for Fine-tuned CLIP"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.04655","kind":"arxiv","version":4},"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:d0fb9c0dfceca8900f0bb6e7c32bb6d904e1c56b3921ea7d5b30555e8a4f46fe","target":"record","created_at":"2026-07-05T08:31:48Z","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":"04335c94f8d5c95d7358a2feca93b6d43332d08ddaf87f8358b025da386b68ae","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-07T08:42:48Z","title_canon_sha256":"97a24c593545837e838b840821f82912291dc09658837ff7f05f1f4fb66481a5"},"schema_version":"1.0","source":{"id":"2402.04655","kind":"arxiv","version":4}},"canonical_sha256":"f906630ebfc97ecb3cf1a2d882bd83389a4b26063b245ed2dabde1719af305e4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f906630ebfc97ecb3cf1a2d882bd83389a4b26063b245ed2dabde1719af305e4","first_computed_at":"2026-07-05T08:31:48.252896Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:31:48.252896Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6mwAGD1R7WW7sPKoiWzXyUHEW3qJryqbkf0KqzZtPP1KU0qVqF/hVbIrtvxC6mE3yo3hL61lWYqpr1wUy4laBA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:31:48.253393Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.04655","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d0fb9c0dfceca8900f0bb6e7c32bb6d904e1c56b3921ea7d5b30555e8a4f46fe","sha256:eb0dd1207c4ef2d0d7223866a141eb30d63164ead123bd39ad4315bbc7b9091c"],"state_sha256":"861a9f1f903fc5600f77c2c3a3b536ca761b63855648cfc5b28b93f26dca8de7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7CL9vnDJvy7EfuOKxpoNoIkun3UzR+w5gpQRLrqwMle1MdXIQJw8xRsApAC2iSoxN0hmerQh0mbDgyAO+q+cDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T17:06:28.485510Z","bundle_sha256":"cf236905e15e9ecdcc6c8d7d1246fa15629831ad27a327cfcbb06a2f7492a26d"}}