{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:HAXJKXGJB6J5MJ6PRVTU2T3P4R","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":"b037dff18e44bbfbf66f7ed9eb63bd6bf762a80f19063c7de20719e1a21e047d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-07T17:32:55Z","title_canon_sha256":"5a3c3d211d0a02e90db4f0f0156d8a6217c34e5d9b64ae014bcf593b446b4fff"},"schema_version":"1.0","source":{"id":"2311.04157","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.04157","created_at":"2026-07-05T08:31:44Z"},{"alias_kind":"arxiv_version","alias_value":"2311.04157v3","created_at":"2026-07-05T08:31:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.04157","created_at":"2026-07-05T08:31:44Z"},{"alias_kind":"pith_short_12","alias_value":"HAXJKXGJB6J5","created_at":"2026-07-05T08:31:44Z"},{"alias_kind":"pith_short_16","alias_value":"HAXJKXGJB6J5MJ6P","created_at":"2026-07-05T08:31:44Z"},{"alias_kind":"pith_short_8","alias_value":"HAXJKXGJ","created_at":"2026-07-05T08:31:44Z"}],"graph_snapshots":[{"event_id":"sha256:c72b91c79f5c9e3e2500af9f7ce1842359a394cf26645ca89eef262a62e502f0","target":"graph","created_at":"2026-07-05T08:31:44Z","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/2311.04157/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a novel usage of Transformers to make image classification interpretable. Unlike mainstream classifiers that wait until the last fully connected layer to incorporate class information to make predictions, we investigate a proactive approach, asking each class to search for itself in an image. We realize this idea via a Transformer encoder-decoder inspired by DEtection TRansformer (DETR). We learn \"class-specific\" queries (one for each class) as input to the decoder, enabling each class to localize its patterns in an image via cross-attention. We name our approach INterpretable TRans","authors_text":"Anuj Karpatne, Arpita Chowdhury, Bryan Carstens, Charles Stewart, Daniel Rubenstein, David Carlyn, Dipanjyoti Paul, Feng-Ju Chang, Kaiya L. Provost, Samuel Stevens, Tanya Berger-Wolf, Wei-Lun Chao, Xinqi Xiong, Yu Su","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-07T17:32:55Z","title":"A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.04157","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":"sha256:898fe7b3d28c7bb7551593abcff4715dc80bbf3488e796ac4ddc40b50fb9e1f2","target":"record","created_at":"2026-07-05T08:31:44Z","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":"b037dff18e44bbfbf66f7ed9eb63bd6bf762a80f19063c7de20719e1a21e047d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-07T17:32:55Z","title_canon_sha256":"5a3c3d211d0a02e90db4f0f0156d8a6217c34e5d9b64ae014bcf593b446b4fff"},"schema_version":"1.0","source":{"id":"2311.04157","kind":"arxiv","version":3}},"canonical_sha256":"382e955cc90f93d627cf8d674d4f6fe475c194b478c700a751461918a3136941","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"382e955cc90f93d627cf8d674d4f6fe475c194b478c700a751461918a3136941","first_computed_at":"2026-07-05T08:31:44.324370Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:31:44.324370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8GZLxOcyo+b+6CXfTkrSTO2VxaN2tz6NiQtP/ROyCLf7SPGu/k35M3rgp0LQO46WAljGe4daMLz9DnNAargRDA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:31:44.324872Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.04157","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:898fe7b3d28c7bb7551593abcff4715dc80bbf3488e796ac4ddc40b50fb9e1f2","sha256:c72b91c79f5c9e3e2500af9f7ce1842359a394cf26645ca89eef262a62e502f0"],"state_sha256":"1d7e0d2ad695817ec34a0600b1c3180459da75fa3ef4182794f057d75bd1f68c"}