{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:6KPILVCSSOXWAP46TIFNQYMX6M","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":"58a6b2e9b851e0588784bbb6ede73259cad3133ae289d9dc1328afa54c52d4f6","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-03T02:40:34Z","title_canon_sha256":"0f004b26f902e6c4a225282c7e762d436945b13d6725e7cf8ca3309720192a27"},"schema_version":"1.0","source":{"id":"2207.00938","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.00938","created_at":"2026-07-05T05:19:17Z"},{"alias_kind":"arxiv_version","alias_value":"2207.00938v2","created_at":"2026-07-05T05:19:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.00938","created_at":"2026-07-05T05:19:17Z"},{"alias_kind":"pith_short_12","alias_value":"6KPILVCSSOXW","created_at":"2026-07-05T05:19:17Z"},{"alias_kind":"pith_short_16","alias_value":"6KPILVCSSOXWAP46","created_at":"2026-07-05T05:19:17Z"},{"alias_kind":"pith_short_8","alias_value":"6KPILVCS","created_at":"2026-07-05T05:19:17Z"}],"graph_snapshots":[{"event_id":"sha256:1393478bc4ae6c1e1ae12145bd0c693e6d34aadb3fe1ef4b51ed30bc17b56fe0","target":"graph","created_at":"2026-07-05T05:19:17Z","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/2207.00938/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"There is a growing concern about typically opaque decision-making with high-performance machine learning algorithms. Providing an explanation of the reasoning process in domain-specific terms can be crucial for adoption in risk-sensitive domains such as healthcare. We argue that machine learning algorithms should be interpretable by design and that the language in which these interpretations are expressed should be domain- and task-dependent. Consequently, we base our model's prediction on a family of user-defined and task-specific binary functions of the data, each having a clear interpretati","authors_text":"Aditya Chattopadhyay, Benjamin D. Haeffele, Donald Geman, Rene Vidal, Stewart Slocum","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-03T02:40:34Z","title":"Interpretable by Design: Learning Predictors by Composing Interpretable Queries"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.00938","kind":"arxiv","version":2},"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":"sha256:0dfd90515e6e977985c41d20ed2d881c0ed1ce6830d345e1358cb42c9754fa49","target":"record","created_at":"2026-07-05T05:19:17Z","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":"58a6b2e9b851e0588784bbb6ede73259cad3133ae289d9dc1328afa54c52d4f6","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-03T02:40:34Z","title_canon_sha256":"0f004b26f902e6c4a225282c7e762d436945b13d6725e7cf8ca3309720192a27"},"schema_version":"1.0","source":{"id":"2207.00938","kind":"arxiv","version":2}},"canonical_sha256":"f29e85d45293af603f9e9a0ad86197f30d2393afe152a4cd7c8da10450c1e49d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f29e85d45293af603f9e9a0ad86197f30d2393afe152a4cd7c8da10450c1e49d","first_computed_at":"2026-07-05T05:19:17.403403Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:19:17.403403Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MYjHIV9IRv4kwWyUn3NiiQkhK/FtvbOPQTlXp/XvJGNCHAWBAgjsFK97I6asH2riaZPx3mcrJsDQg/yQxNuWAA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:19:17.403800Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.00938","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0dfd90515e6e977985c41d20ed2d881c0ed1ce6830d345e1358cb42c9754fa49","sha256:1393478bc4ae6c1e1ae12145bd0c693e6d34aadb3fe1ef4b51ed30bc17b56fe0"],"state_sha256":"ab06a3e7990ba915ae89242eed2964600564cca81833e1a9700042a42518c457"}