{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:BW4RJOY33SE7T3RJHHG45UFJWJ","short_pith_number":"pith:BW4RJOY3","schema_version":"1.0","canonical_sha256":"0db914bb1bdc89f9ee2939cdced0a9b2708e53dc4b66b3f8988fe42084a4df9d","source":{"kind":"arxiv","id":"2307.14517","version":1},"attestation_state":"computed","paper":{"title":"The Co-12 Recipe for Evaluating Interpretable Part-Prototype Image Classifiers","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Christin Seifert, Meike Nauta","submitted_at":"2023-07-26T21:33:35Z","abstract_excerpt":"Interpretable part-prototype models are computer vision models that are explainable by design. The models learn prototypical parts and recognise these components in an image, thereby combining classification and explanation. Despite the recent attention for intrinsically interpretable models, there is no comprehensive overview on evaluating the explanation quality of interpretable part-prototype models. Based on the Co-12 properties for explanation quality as introduced in arXiv:2201.08164 (e.g., correctness, completeness, compactness), we review existing work that evaluates part-prototype mod"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2307.14517","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-07-26T21:33:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ca703975448fed21b013a1a2bdce00b7b378b277e21afdc95f95003040f3d143","abstract_canon_sha256":"ac0715750ad9d301d7d0356bc4634b9ccd9063679eda8081b18cdb29b56fae28"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:35:14.176220Z","signature_b64":"BQA0kGp4GvAWqF5p546SbiMg/d54KbPcxqzcUUBHjT6ky06AC30lXU5o/w1FG+tZw9/7dsZpXjsmAGlV49BxAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0db914bb1bdc89f9ee2939cdced0a9b2708e53dc4b66b3f8988fe42084a4df9d","last_reissued_at":"2026-07-05T06:35:14.175815Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:35:14.175815Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The Co-12 Recipe for Evaluating Interpretable Part-Prototype Image Classifiers","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Christin Seifert, Meike Nauta","submitted_at":"2023-07-26T21:33:35Z","abstract_excerpt":"Interpretable part-prototype models are computer vision models that are explainable by design. The models learn prototypical parts and recognise these components in an image, thereby combining classification and explanation. Despite the recent attention for intrinsically interpretable models, there is no comprehensive overview on evaluating the explanation quality of interpretable part-prototype models. Based on the Co-12 properties for explanation quality as introduced in arXiv:2201.08164 (e.g., correctness, completeness, compactness), we review existing work that evaluates part-prototype mod"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.14517","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/2307.14517/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2307.14517","created_at":"2026-07-05T06:35:14.175878+00:00"},{"alias_kind":"arxiv_version","alias_value":"2307.14517v1","created_at":"2026-07-05T06:35:14.175878+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.14517","created_at":"2026-07-05T06:35:14.175878+00:00"},{"alias_kind":"pith_short_12","alias_value":"BW4RJOY33SE7","created_at":"2026-07-05T06:35:14.175878+00:00"},{"alias_kind":"pith_short_16","alias_value":"BW4RJOY33SE7T3RJ","created_at":"2026-07-05T06:35:14.175878+00:00"},{"alias_kind":"pith_short_8","alias_value":"BW4RJOY3","created_at":"2026-07-05T06:35:14.175878+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/BW4RJOY33SE7T3RJHHG45UFJWJ","json":"https://pith.science/pith/BW4RJOY33SE7T3RJHHG45UFJWJ.json","graph_json":"https://pith.science/api/pith-number/BW4RJOY33SE7T3RJHHG45UFJWJ/graph.json","events_json":"https://pith.science/api/pith-number/BW4RJOY33SE7T3RJHHG45UFJWJ/events.json","paper":"https://pith.science/paper/BW4RJOY3"},"agent_actions":{"view_html":"https://pith.science/pith/BW4RJOY33SE7T3RJHHG45UFJWJ","download_json":"https://pith.science/pith/BW4RJOY33SE7T3RJHHG45UFJWJ.json","view_paper":"https://pith.science/paper/BW4RJOY3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2307.14517&json=true","fetch_graph":"https://pith.science/api/pith-number/BW4RJOY33SE7T3RJHHG45UFJWJ/graph.json","fetch_events":"https://pith.science/api/pith-number/BW4RJOY33SE7T3RJHHG45UFJWJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BW4RJOY33SE7T3RJHHG45UFJWJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BW4RJOY33SE7T3RJHHG45UFJWJ/action/storage_attestation","attest_author":"https://pith.science/pith/BW4RJOY33SE7T3RJHHG45UFJWJ/action/author_attestation","sign_citation":"https://pith.science/pith/BW4RJOY33SE7T3RJHHG45UFJWJ/action/citation_signature","submit_replication":"https://pith.science/pith/BW4RJOY33SE7T3RJHHG45UFJWJ/action/replication_record"}},"created_at":"2026-07-05T06:35:14.175878+00:00","updated_at":"2026-07-05T06:35:14.175878+00:00"}