{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:4N4JC73D4MOVZSEZTQESZZ3SXP","short_pith_number":"pith:4N4JC73D","canonical_record":{"source":{"id":"2402.02933","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-05T11:55:50Z","cross_cats_sorted":["cs.CY","cs.HC"],"title_canon_sha256":"f0182538ff7ae2c575cd1a011c9fefe7d0607382830c5b240d7bf0e8aa2a55ca","abstract_canon_sha256":"146506933d59f5c050993340881c4914933b784b18312f1c3ae05423d7aaae20"},"schema_version":"1.0"},"canonical_sha256":"e378917f63e31d5cc8999c092ce772bbc1eccf9de4891d9644dac5d25d573d92","source":{"kind":"arxiv","id":"2402.02933","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.02933","created_at":"2026-07-05T11:11:20Z"},{"alias_kind":"arxiv_version","alias_value":"2402.02933v4","created_at":"2026-07-05T11:11:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.02933","created_at":"2026-07-05T11:11:20Z"},{"alias_kind":"pith_short_12","alias_value":"4N4JC73D4MOV","created_at":"2026-07-05T11:11:20Z"},{"alias_kind":"pith_short_16","alias_value":"4N4JC73D4MOVZSEZ","created_at":"2026-07-05T11:11:20Z"},{"alias_kind":"pith_short_8","alias_value":"4N4JC73D","created_at":"2026-07-05T11:11:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:4N4JC73D4MOVZSEZTQESZZ3SXP","target":"record","payload":{"canonical_record":{"source":{"id":"2402.02933","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-05T11:55:50Z","cross_cats_sorted":["cs.CY","cs.HC"],"title_canon_sha256":"f0182538ff7ae2c575cd1a011c9fefe7d0607382830c5b240d7bf0e8aa2a55ca","abstract_canon_sha256":"146506933d59f5c050993340881c4914933b784b18312f1c3ae05423d7aaae20"},"schema_version":"1.0"},"canonical_sha256":"e378917f63e31d5cc8999c092ce772bbc1eccf9de4891d9644dac5d25d573d92","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:11:20.165337Z","signature_b64":"cUvFFS+DXEP82vJquwjAak+DFQF1e1BKe/L1TBsX7EN0H0Fccca2MJw4HX1h3DCwxirWDt2PK+vyoXtcycEPBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e378917f63e31d5cc8999c092ce772bbc1eccf9de4891d9644dac5d25d573d92","last_reissued_at":"2026-07-05T11:11:20.164839Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:11:20.164839Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.02933","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:11:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/PfbXNLO9D+3OMtnikC3e9kUaRHABr0FcuVh+Ph5YBXpdTXHI3K28eejLWXzrKIl08w/22sEC+dFYyxbWa7QDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T21:15:08.290751Z"},"content_sha256":"70730ed7f3d09f981b4cd73225dafdaff5a03fad507e9bb19e08239dc9a704ff","schema_version":"1.0","event_id":"sha256:70730ed7f3d09f981b4cd73225dafdaff5a03fad507e9bb19e08239dc9a704ff"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:4N4JC73D4MOVZSEZTQESZZ3SXP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Intrinsic User-Centric Interpretability through Global Mixture of Experts","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CY","cs.HC"],"primary_cat":"cs.LG","authors_text":"Jibril Frej, Julian Blackwell, Martin Jaggi, Syrielle Montariol, Tanja K\\\"aser, Vinitra Swamy","submitted_at":"2024-02-05T11:55:50Z","abstract_excerpt":"In human-centric settings like education or healthcare, model accuracy and model explainability are key factors for user adoption. Towards these two goals, intrinsically interpretable deep learning models have gained popularity, focusing on accurate predictions alongside faithful explanations. However, there exists a gap in the human-centeredness of these approaches, which often produce nuanced and complex explanations that are not easily actionable for downstream users. We present InterpretCC (interpretable conditional computation), a family of intrinsically interpretable neural networks at a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.02933","kind":"arxiv","version":4},"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/2402.02933/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":"2026-07-05T11:11:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HhflWP9L8esIVLO9MYffilW3D70n31rWbZToX2Mg4g1/25gTX5de4gH4Er1dZelESvu4LhiqvRRMoGW1Z5RqBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T21:15:08.291263Z"},"content_sha256":"7c85d5417d6625b941900b694ef90c67e27518dcb3b5b8ef9b9f0cc50c450c3a","schema_version":"1.0","event_id":"sha256:7c85d5417d6625b941900b694ef90c67e27518dcb3b5b8ef9b9f0cc50c450c3a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4N4JC73D4MOVZSEZTQESZZ3SXP/bundle.json","state_url":"https://pith.science/pith/4N4JC73D4MOVZSEZTQESZZ3SXP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4N4JC73D4MOVZSEZTQESZZ3SXP/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":"2026-08-15T21:15:08Z","links":{"resolver":"https://pith.science/pith/4N4JC73D4MOVZSEZTQESZZ3SXP","bundle":"https://pith.science/pith/4N4JC73D4MOVZSEZTQESZZ3SXP/bundle.json","state":"https://pith.science/pith/4N4JC73D4MOVZSEZTQESZZ3SXP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4N4JC73D4MOVZSEZTQESZZ3SXP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4N4JC73D4MOVZSEZTQESZZ3SXP","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":"146506933d59f5c050993340881c4914933b784b18312f1c3ae05423d7aaae20","cross_cats_sorted":["cs.CY","cs.HC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-05T11:55:50Z","title_canon_sha256":"f0182538ff7ae2c575cd1a011c9fefe7d0607382830c5b240d7bf0e8aa2a55ca"},"schema_version":"1.0","source":{"id":"2402.02933","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.02933","created_at":"2026-07-05T11:11:20Z"},{"alias_kind":"arxiv_version","alias_value":"2402.02933v4","created_at":"2026-07-05T11:11:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.02933","created_at":"2026-07-05T11:11:20Z"},{"alias_kind":"pith_short_12","alias_value":"4N4JC73D4MOV","created_at":"2026-07-05T11:11:20Z"},{"alias_kind":"pith_short_16","alias_value":"4N4JC73D4MOVZSEZ","created_at":"2026-07-05T11:11:20Z"},{"alias_kind":"pith_short_8","alias_value":"4N4JC73D","created_at":"2026-07-05T11:11:20Z"}],"graph_snapshots":[{"event_id":"sha256:7c85d5417d6625b941900b694ef90c67e27518dcb3b5b8ef9b9f0cc50c450c3a","target":"graph","created_at":"2026-07-05T11:11:20Z","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/2402.02933/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In human-centric settings like education or healthcare, model accuracy and model explainability are key factors for user adoption. Towards these two goals, intrinsically interpretable deep learning models have gained popularity, focusing on accurate predictions alongside faithful explanations. However, there exists a gap in the human-centeredness of these approaches, which often produce nuanced and complex explanations that are not easily actionable for downstream users. We present InterpretCC (interpretable conditional computation), a family of intrinsically interpretable neural networks at a","authors_text":"Jibril Frej, Julian Blackwell, Martin Jaggi, Syrielle Montariol, Tanja K\\\"aser, Vinitra Swamy","cross_cats":["cs.CY","cs.HC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-05T11:55:50Z","title":"Intrinsic User-Centric Interpretability through Global Mixture of Experts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.02933","kind":"arxiv","version":4},"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":"sha256:70730ed7f3d09f981b4cd73225dafdaff5a03fad507e9bb19e08239dc9a704ff","target":"record","created_at":"2026-07-05T11:11:20Z","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":"146506933d59f5c050993340881c4914933b784b18312f1c3ae05423d7aaae20","cross_cats_sorted":["cs.CY","cs.HC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-05T11:55:50Z","title_canon_sha256":"f0182538ff7ae2c575cd1a011c9fefe7d0607382830c5b240d7bf0e8aa2a55ca"},"schema_version":"1.0","source":{"id":"2402.02933","kind":"arxiv","version":4}},"canonical_sha256":"e378917f63e31d5cc8999c092ce772bbc1eccf9de4891d9644dac5d25d573d92","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e378917f63e31d5cc8999c092ce772bbc1eccf9de4891d9644dac5d25d573d92","first_computed_at":"2026-07-05T11:11:20.164839Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:11:20.164839Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cUvFFS+DXEP82vJquwjAak+DFQF1e1BKe/L1TBsX7EN0H0Fccca2MJw4HX1h3DCwxirWDt2PK+vyoXtcycEPBg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:11:20.165337Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.02933","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:70730ed7f3d09f981b4cd73225dafdaff5a03fad507e9bb19e08239dc9a704ff","sha256:7c85d5417d6625b941900b694ef90c67e27518dcb3b5b8ef9b9f0cc50c450c3a"],"state_sha256":"8d929b3dc8f3d257183e0e9e723d51c1f856745afa39bbf2a114abdc2913c7a5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oLthBQC6GQe22d2235bixx7VZiltCOTI89iWVIgIB3tNfZmq8XPum1UeduhL7tkFFgUWBLgo/ezyhQ/DipoUDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T21:15:08.295330Z","bundle_sha256":"aa9f5888f511f5f2335a70c81ed4558da0f9ead78351cd369562a4689dbad153"}}