{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:M5MQ3RCMZ2TIZ35AGY2CYQ5A7N","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":"288f307c1c5de90fae0bd188788bc0f3f503e6b4fb3696bb9191aed05e29a30b","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-06T04:18:18Z","title_canon_sha256":"8bfc0edaa7e9e1b07db05f59396369e1d5149b6cb9218c12db8d1cf61074853a"},"schema_version":"1.0","source":{"id":"2010.02467","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.02467","created_at":"2026-07-05T01:40:50Z"},{"alias_kind":"arxiv_version","alias_value":"2010.02467v1","created_at":"2026-07-05T01:40:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.02467","created_at":"2026-07-05T01:40:50Z"},{"alias_kind":"pith_short_12","alias_value":"M5MQ3RCMZ2TI","created_at":"2026-07-05T01:40:50Z"},{"alias_kind":"pith_short_16","alias_value":"M5MQ3RCMZ2TIZ35A","created_at":"2026-07-05T01:40:50Z"},{"alias_kind":"pith_short_8","alias_value":"M5MQ3RCM","created_at":"2026-07-05T01:40:50Z"}],"graph_snapshots":[{"event_id":"sha256:0ba91e5b0bf74510f72d31ef11e34ee642811d7a2f57c90755efd550f30942a0","target":"graph","created_at":"2026-07-05T01:40:50Z","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/2010.02467/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automatic medical image report generation has drawn growing attention due to its potential to alleviate radiologists' workload. Existing work on report generation often trains encoder-decoder networks to generate complete reports. However, such models are affected by data bias (e.g.~label imbalance) and face common issues inherent in text generation models (e.g.~repetition). In this work, we focus on reporting abnormal findings on radiology images; instead of training on complete radiology reports, we propose a method to identify abnormal findings from the reports in addition to grouping them ","authors_text":"Amilcare Gentili, Chun-Nan Hsu, Jianmo Ni, Julian McAuley","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-06T04:18:18Z","title":"Learning Visual-Semantic Embeddings for Reporting Abnormal Findings on Chest X-rays"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.02467","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":"sha256:33d60810f447455b092378f7825cc20b647a880688c712780ad41aee7860c811","target":"record","created_at":"2026-07-05T01:40:50Z","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":"288f307c1c5de90fae0bd188788bc0f3f503e6b4fb3696bb9191aed05e29a30b","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-06T04:18:18Z","title_canon_sha256":"8bfc0edaa7e9e1b07db05f59396369e1d5149b6cb9218c12db8d1cf61074853a"},"schema_version":"1.0","source":{"id":"2010.02467","kind":"arxiv","version":1}},"canonical_sha256":"67590dc44ccea68cefa036342c43a0fb650f1d11d88c6ef990c288c0c1e08226","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"67590dc44ccea68cefa036342c43a0fb650f1d11d88c6ef990c288c0c1e08226","first_computed_at":"2026-07-05T01:40:50.223188Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:40:50.223188Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IspfDNWXVyUFWGCFOGdVD19wE64bMTRb60m1XRBn97WUHqWsHhMsjeYqnDTOebBnkW/nX5pF/jRHGcYJ/H78Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:40:50.223646Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.02467","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:33d60810f447455b092378f7825cc20b647a880688c712780ad41aee7860c811","sha256:0ba91e5b0bf74510f72d31ef11e34ee642811d7a2f57c90755efd550f30942a0"],"state_sha256":"c371ec29a8fc93d3a4c9a5a385118ee86c836bfc6201df0ffac390cd6d8eca40"}