{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HNCXX2IB4UXM64VBQQV7OGACYM","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":"caa5f885cc58529f531005addc25a9c7a8036133a273b0cd89cb2555f727102c","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-15T17:09:53Z","title_canon_sha256":"922bd52a04426060c90210a311b595783ebd2e8d652a9e88db3e74e55b594ea4"},"schema_version":"1.0","source":{"id":"2404.09941","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.09941","created_at":"2026-07-05T08:08:13Z"},{"alias_kind":"arxiv_version","alias_value":"2404.09941v1","created_at":"2026-07-05T08:08:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.09941","created_at":"2026-07-05T08:08:13Z"},{"alias_kind":"pith_short_12","alias_value":"HNCXX2IB4UXM","created_at":"2026-07-05T08:08:13Z"},{"alias_kind":"pith_short_16","alias_value":"HNCXX2IB4UXM64VB","created_at":"2026-07-05T08:08:13Z"},{"alias_kind":"pith_short_8","alias_value":"HNCXX2IB","created_at":"2026-07-05T08:08:13Z"}],"graph_snapshots":[{"event_id":"sha256:0e2050aabed7de5ca8172b9e54bdd35e5c5d67254b81cedb574229382db1d7bd","target":"graph","created_at":"2026-07-05T08:08:13Z","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/2404.09941/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multimodal pre-trained models, such as CLIP, are popular for zero-shot classification due to their open-vocabulary flexibility and high performance. However, vision-language models, which compute similarity scores between images and class labels, are largely black-box, with limited interpretability, risk for bias, and inability to discover new visual concepts not written down. Moreover, in practical settings, the vocabulary for class names and attributes of specialized concepts will not be known, preventing these methods from performing well on images uncommon in large-scale vision-language da","authors_text":"Carl Vondrick, Mia Chiquier, Utkarsh Mall","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-15T17:09:53Z","title":"Evolving Interpretable Visual Classifiers with Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.09941","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":"sha256:4360e8562174094279f1b12282307af05ed30a8c1aaf4878b4ec5769288d04df","target":"record","created_at":"2026-07-05T08:08:13Z","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":"caa5f885cc58529f531005addc25a9c7a8036133a273b0cd89cb2555f727102c","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-15T17:09:53Z","title_canon_sha256":"922bd52a04426060c90210a311b595783ebd2e8d652a9e88db3e74e55b594ea4"},"schema_version":"1.0","source":{"id":"2404.09941","kind":"arxiv","version":1}},"canonical_sha256":"3b457be901e52ecf72a1842bf71802c33fdd9475c27f4210a1ec0b0746160fc4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3b457be901e52ecf72a1842bf71802c33fdd9475c27f4210a1ec0b0746160fc4","first_computed_at":"2026-07-05T08:08:13.409745Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:08:13.409745Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1E6/3ddto7jXpZP5QAKdsVf08peka09uqdMSRYUezc//fFVAWesY3DqfO2V7/CfU7r1O2fiNI8O81X1cLmZ3BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:08:13.410205Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.09941","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4360e8562174094279f1b12282307af05ed30a8c1aaf4878b4ec5769288d04df","sha256:0e2050aabed7de5ca8172b9e54bdd35e5c5d67254b81cedb574229382db1d7bd"],"state_sha256":"f88bc9ef67f92b8b809d29bf35b12ad830abc6d5f46374c49a44d34eb2859692"}