{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:OXY3CVVJ3G3GR23ZLYGOAQZR44","short_pith_number":"pith:OXY3CVVJ","canonical_record":{"source":{"id":"2408.01432","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-07-18T19:44:44Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"05849b1f456585c5fe6999a9776bc32ed03c6e3ef7969421fb56a160885abee3","abstract_canon_sha256":"6d46d11582c8d7a651d607927cf2d4f1da3ced5cea3df8697c2f006a8a3f2253"},"schema_version":"1.0"},"canonical_sha256":"75f1b156a9d9b668eb795e0ce04331e732fcddc983ab2c9cdbd1760dcb57f3cf","source":{"kind":"arxiv","id":"2408.01432","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.01432","created_at":"2026-07-05T10:01:35Z"},{"alias_kind":"arxiv_version","alias_value":"2408.01432v3","created_at":"2026-07-05T10:01:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.01432","created_at":"2026-07-05T10:01:35Z"},{"alias_kind":"pith_short_12","alias_value":"OXY3CVVJ3G3G","created_at":"2026-07-05T10:01:35Z"},{"alias_kind":"pith_short_16","alias_value":"OXY3CVVJ3G3GR23Z","created_at":"2026-07-05T10:01:35Z"},{"alias_kind":"pith_short_8","alias_value":"OXY3CVVJ","created_at":"2026-07-05T10:01:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:OXY3CVVJ3G3GR23ZLYGOAQZR44","target":"record","payload":{"canonical_record":{"source":{"id":"2408.01432","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-07-18T19:44:44Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"05849b1f456585c5fe6999a9776bc32ed03c6e3ef7969421fb56a160885abee3","abstract_canon_sha256":"6d46d11582c8d7a651d607927cf2d4f1da3ced5cea3df8697c2f006a8a3f2253"},"schema_version":"1.0"},"canonical_sha256":"75f1b156a9d9b668eb795e0ce04331e732fcddc983ab2c9cdbd1760dcb57f3cf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:01:35.151668Z","signature_b64":"P5GkJXM9X1y7WUSEgvfUtW+jZl1JAR/B2sWvnHcIATpGRiNZm9uRbb8N09uNSEzHhrP0yN6qHuPmBSiT8DLwDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"75f1b156a9d9b668eb795e0ce04331e732fcddc983ab2c9cdbd1760dcb57f3cf","last_reissued_at":"2026-07-05T10:01:35.151231Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:01:35.151231Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.01432","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:01:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6jBOh7SmSngwCn4GvXmqVFBNDtYPnmluBYXyOi7T6wYu8yT+JmFBSNd0jXSUySv56c3HGmayYIUNWyt1slYcDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T00:54:26.682733Z"},"content_sha256":"d5784ac4c67909ab8003044cc508c40dece4cc8c755e6af457a199a87dcf0756","schema_version":"1.0","event_id":"sha256:d5784ac4c67909ab8003044cc508c40dece4cc8c755e6af457a199a87dcf0756"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:OXY3CVVJ3G3GR23ZLYGOAQZR44","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Divyansh Srivastava, Ge Yan, Tsui-Wei Weng","submitted_at":"2024-07-18T19:44:44Z","abstract_excerpt":"Concept Bottleneck Models (CBMs) provide interpretable prediction by introducing an intermediate Concept Bottleneck Layer (CBL), which encodes human-understandable concepts to explain models' decision. Recent works proposed to utilize Large Language Models and pre-trained Vision-Language Models to automate the training of CBMs, making it more scalable and automated. However, existing approaches still fall short in two aspects: First, the concepts predicted by CBL often mismatch the input image, raising doubts about the faithfulness of interpretation. Second, it has been shown that concept valu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.01432","kind":"arxiv","version":3},"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/2408.01432/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":"2026-07-05T10:01:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"POk+UMLwlVuS+Ht/rqNaGBCunczKJlKGZw/LwELXWCxJHJ0ZxBLM2+52wTyZt4UEQCu7g5ePYImHc1ki+EhGDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T00:54:26.683586Z"},"content_sha256":"f36e58b1d7505b33c0d461ce742607e0ef418e2e4a7ef81e47ce7dc754eb2579","schema_version":"1.0","event_id":"sha256:f36e58b1d7505b33c0d461ce742607e0ef418e2e4a7ef81e47ce7dc754eb2579"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OXY3CVVJ3G3GR23ZLYGOAQZR44/bundle.json","state_url":"https://pith.science/pith/OXY3CVVJ3G3GR23ZLYGOAQZR44/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OXY3CVVJ3G3GR23ZLYGOAQZR44/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":"2026-08-19T00:54:26Z","links":{"resolver":"https://pith.science/pith/OXY3CVVJ3G3GR23ZLYGOAQZR44","bundle":"https://pith.science/pith/OXY3CVVJ3G3GR23ZLYGOAQZR44/bundle.json","state":"https://pith.science/pith/OXY3CVVJ3G3GR23ZLYGOAQZR44/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OXY3CVVJ3G3GR23ZLYGOAQZR44/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OXY3CVVJ3G3GR23ZLYGOAQZR44","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":"6d46d11582c8d7a651d607927cf2d4f1da3ced5cea3df8697c2f006a8a3f2253","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-07-18T19:44:44Z","title_canon_sha256":"05849b1f456585c5fe6999a9776bc32ed03c6e3ef7969421fb56a160885abee3"},"schema_version":"1.0","source":{"id":"2408.01432","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.01432","created_at":"2026-07-05T10:01:35Z"},{"alias_kind":"arxiv_version","alias_value":"2408.01432v3","created_at":"2026-07-05T10:01:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.01432","created_at":"2026-07-05T10:01:35Z"},{"alias_kind":"pith_short_12","alias_value":"OXY3CVVJ3G3G","created_at":"2026-07-05T10:01:35Z"},{"alias_kind":"pith_short_16","alias_value":"OXY3CVVJ3G3GR23Z","created_at":"2026-07-05T10:01:35Z"},{"alias_kind":"pith_short_8","alias_value":"OXY3CVVJ","created_at":"2026-07-05T10:01:35Z"}],"graph_snapshots":[{"event_id":"sha256:f36e58b1d7505b33c0d461ce742607e0ef418e2e4a7ef81e47ce7dc754eb2579","target":"graph","created_at":"2026-07-05T10:01:35Z","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/2408.01432/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Concept Bottleneck Models (CBMs) provide interpretable prediction by introducing an intermediate Concept Bottleneck Layer (CBL), which encodes human-understandable concepts to explain models' decision. Recent works proposed to utilize Large Language Models and pre-trained Vision-Language Models to automate the training of CBMs, making it more scalable and automated. However, existing approaches still fall short in two aspects: First, the concepts predicted by CBL often mismatch the input image, raising doubts about the faithfulness of interpretation. Second, it has been shown that concept valu","authors_text":"Divyansh Srivastava, Ge Yan, Tsui-Wei Weng","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-07-18T19:44:44Z","title":"VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.01432","kind":"arxiv","version":3},"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:d5784ac4c67909ab8003044cc508c40dece4cc8c755e6af457a199a87dcf0756","target":"record","created_at":"2026-07-05T10:01:35Z","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":"6d46d11582c8d7a651d607927cf2d4f1da3ced5cea3df8697c2f006a8a3f2253","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-07-18T19:44:44Z","title_canon_sha256":"05849b1f456585c5fe6999a9776bc32ed03c6e3ef7969421fb56a160885abee3"},"schema_version":"1.0","source":{"id":"2408.01432","kind":"arxiv","version":3}},"canonical_sha256":"75f1b156a9d9b668eb795e0ce04331e732fcddc983ab2c9cdbd1760dcb57f3cf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"75f1b156a9d9b668eb795e0ce04331e732fcddc983ab2c9cdbd1760dcb57f3cf","first_computed_at":"2026-07-05T10:01:35.151231Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:01:35.151231Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"P5GkJXM9X1y7WUSEgvfUtW+jZl1JAR/B2sWvnHcIATpGRiNZm9uRbb8N09uNSEzHhrP0yN6qHuPmBSiT8DLwDw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:01:35.151668Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.01432","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d5784ac4c67909ab8003044cc508c40dece4cc8c755e6af457a199a87dcf0756","sha256:f36e58b1d7505b33c0d461ce742607e0ef418e2e4a7ef81e47ce7dc754eb2579"],"state_sha256":"fb24cade41a408dea5f9347552d6fa6ea09b2dc8a9ac356e26377c50a86ab52a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MctGCzqP+emo5+WJtPVg+teTyfs0euZ3DG1DXXrNqvELECLqTG34fPZGHpik8/UZXCTCMtatxhDsnKKllGrVBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T00:54:26.690070Z","bundle_sha256":"6bec49163f9a7da920c481d0fd6194b0da14d4663a5c48ee4784dcd558df1bdc"}}