{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:INEBGHFPITEHS3YPYNPXIT6ZZP","short_pith_number":"pith:INEBGHFP","canonical_record":{"source":{"id":"2406.19130","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-27T12:29:50Z","cross_cats_sorted":[],"title_canon_sha256":"eaa3b8430c961ba6b3ab503b2fff49f86ae63f35fc58ad0aaee98dd5f795fe16","abstract_canon_sha256":"fc9ada3d370eb2a487a6c192f472931005d05e116894a29184111450457e2a2f"},"schema_version":"1.0"},"canonical_sha256":"4348131caf44c8796f0fc35f744fd9cbfd7fab42398a078aab96303c62c46996","source":{"kind":"arxiv","id":"2406.19130","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.19130","created_at":"2026-07-05T08:37:30Z"},{"alias_kind":"arxiv_version","alias_value":"2406.19130v1","created_at":"2026-07-05T08:37:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.19130","created_at":"2026-07-05T08:37:30Z"},{"alias_kind":"pith_short_12","alias_value":"INEBGHFPITEH","created_at":"2026-07-05T08:37:30Z"},{"alias_kind":"pith_short_16","alias_value":"INEBGHFPITEHS3YP","created_at":"2026-07-05T08:37:30Z"},{"alias_kind":"pith_short_8","alias_value":"INEBGHFP","created_at":"2026-07-05T08:37:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:INEBGHFPITEHS3YPYNPXIT6ZZP","target":"record","payload":{"canonical_record":{"source":{"id":"2406.19130","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-27T12:29:50Z","cross_cats_sorted":[],"title_canon_sha256":"eaa3b8430c961ba6b3ab503b2fff49f86ae63f35fc58ad0aaee98dd5f795fe16","abstract_canon_sha256":"fc9ada3d370eb2a487a6c192f472931005d05e116894a29184111450457e2a2f"},"schema_version":"1.0"},"canonical_sha256":"4348131caf44c8796f0fc35f744fd9cbfd7fab42398a078aab96303c62c46996","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:37:30.514298Z","signature_b64":"0i0JAIn3W6Xtx5T2p8yDJ9V683a0sGFYWZJzB22lGbSBpwGUhJ1YToDtCcFyH9F3OHXIJHg5wcPNWZmjUyC0BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4348131caf44c8796f0fc35f744fd9cbfd7fab42398a078aab96303c62c46996","last_reissued_at":"2026-07-05T08:37:30.513888Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:37:30.513888Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.19130","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:37:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CXMDc7rRm9C3dISivV6WYmCu/VTB9EyT61vPa+Zaj3LqWuzd1fz+yC7IjP0A0HY+oGvFBrTDYTuq1FXMfnzOBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:05:20.317709Z"},"content_sha256":"8736ecb7da6a28e33e8f0b8b158c14f20294003b0729df8828f6488f845d3bd3","schema_version":"1.0","event_id":"sha256:8736ecb7da6a28e33e8f0b8b158c14f20294003b0729df8828f6488f845d3bd3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:INEBGHFPITEHS3YPYNPXIT6ZZP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evidential Concept Embedding Models: Towards Reliable Concept Explanations for Skin Disease Diagnosis","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bomin Wang, Xiahai Zhuang, Xin Gao, Yibo Gao, Yuanye Liu, Zheyao Gao","submitted_at":"2024-06-27T12:29:50Z","abstract_excerpt":"Due to the high stakes in medical decision-making, there is a compelling demand for interpretable deep learning methods in medical image analysis. Concept Bottleneck Models (CBM) have emerged as an active interpretable framework incorporating human-interpretable concepts into decision-making. However, their concept predictions may lack reliability when applied to clinical diagnosis, impeding concept explanations' quality. To address this, we propose an evidential Concept Embedding Model (evi-CEM), which employs evidential learning to model the concept uncertainty. Additionally, we offer to lev"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.19130","kind":"arxiv","version":1},"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/2406.19130/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":"2026-07-05T08:37:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m0SUhp6Ih8ILApuoRigu8+Yyd7WxTEjA4LUUM8MmMJMU3tqqA/6OQPMHWgkaSvx70Et39fd1rtpJsOAStZb+AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:05:20.319112Z"},"content_sha256":"b43578f54b01a90671a71ff178956209250c7279fb7bf4906b4f96515e334491","schema_version":"1.0","event_id":"sha256:b43578f54b01a90671a71ff178956209250c7279fb7bf4906b4f96515e334491"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/INEBGHFPITEHS3YPYNPXIT6ZZP/bundle.json","state_url":"https://pith.science/pith/INEBGHFPITEHS3YPYNPXIT6ZZP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/INEBGHFPITEHS3YPYNPXIT6ZZP/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":"2026-08-06T19:05:20Z","links":{"resolver":"https://pith.science/pith/INEBGHFPITEHS3YPYNPXIT6ZZP","bundle":"https://pith.science/pith/INEBGHFPITEHS3YPYNPXIT6ZZP/bundle.json","state":"https://pith.science/pith/INEBGHFPITEHS3YPYNPXIT6ZZP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/INEBGHFPITEHS3YPYNPXIT6ZZP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:INEBGHFPITEHS3YPYNPXIT6ZZP","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":"fc9ada3d370eb2a487a6c192f472931005d05e116894a29184111450457e2a2f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-27T12:29:50Z","title_canon_sha256":"eaa3b8430c961ba6b3ab503b2fff49f86ae63f35fc58ad0aaee98dd5f795fe16"},"schema_version":"1.0","source":{"id":"2406.19130","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.19130","created_at":"2026-07-05T08:37:30Z"},{"alias_kind":"arxiv_version","alias_value":"2406.19130v1","created_at":"2026-07-05T08:37:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.19130","created_at":"2026-07-05T08:37:30Z"},{"alias_kind":"pith_short_12","alias_value":"INEBGHFPITEH","created_at":"2026-07-05T08:37:30Z"},{"alias_kind":"pith_short_16","alias_value":"INEBGHFPITEHS3YP","created_at":"2026-07-05T08:37:30Z"},{"alias_kind":"pith_short_8","alias_value":"INEBGHFP","created_at":"2026-07-05T08:37:30Z"}],"graph_snapshots":[{"event_id":"sha256:b43578f54b01a90671a71ff178956209250c7279fb7bf4906b4f96515e334491","target":"graph","created_at":"2026-07-05T08:37:30Z","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/2406.19130/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Due to the high stakes in medical decision-making, there is a compelling demand for interpretable deep learning methods in medical image analysis. Concept Bottleneck Models (CBM) have emerged as an active interpretable framework incorporating human-interpretable concepts into decision-making. However, their concept predictions may lack reliability when applied to clinical diagnosis, impeding concept explanations' quality. To address this, we propose an evidential Concept Embedding Model (evi-CEM), which employs evidential learning to model the concept uncertainty. Additionally, we offer to lev","authors_text":"Bomin Wang, Xiahai Zhuang, Xin Gao, Yibo Gao, Yuanye Liu, Zheyao Gao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-27T12:29:50Z","title":"Evidential Concept Embedding Models: Towards Reliable Concept Explanations for Skin Disease Diagnosis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.19130","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":"sha256:8736ecb7da6a28e33e8f0b8b158c14f20294003b0729df8828f6488f845d3bd3","target":"record","created_at":"2026-07-05T08:37:30Z","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":"fc9ada3d370eb2a487a6c192f472931005d05e116894a29184111450457e2a2f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-27T12:29:50Z","title_canon_sha256":"eaa3b8430c961ba6b3ab503b2fff49f86ae63f35fc58ad0aaee98dd5f795fe16"},"schema_version":"1.0","source":{"id":"2406.19130","kind":"arxiv","version":1}},"canonical_sha256":"4348131caf44c8796f0fc35f744fd9cbfd7fab42398a078aab96303c62c46996","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4348131caf44c8796f0fc35f744fd9cbfd7fab42398a078aab96303c62c46996","first_computed_at":"2026-07-05T08:37:30.513888Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:37:30.513888Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0i0JAIn3W6Xtx5T2p8yDJ9V683a0sGFYWZJzB22lGbSBpwGUhJ1YToDtCcFyH9F3OHXIJHg5wcPNWZmjUyC0BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:37:30.514298Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.19130","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8736ecb7da6a28e33e8f0b8b158c14f20294003b0729df8828f6488f845d3bd3","sha256:b43578f54b01a90671a71ff178956209250c7279fb7bf4906b4f96515e334491"],"state_sha256":"2f637837bf7ea393f024ee85e655d3b8814176cf006c7de99141408d4d3984ea"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MLMwavuDdyiOK1D5A8XwVqDfnKP3BQYn63DvqMYDzB9wxdZCiG9CADwN+vwdAOAw9+DKjSGkpm2yJtdskO7sDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T19:05:20.326095Z","bundle_sha256":"f4faba0305d23fc2c418e51735c3a77dc93101e08e706f6ef9cbd9e230378723"}}