{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:ULJ6JKB7IG3YDQJF6Y4U7ZLHOS","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":"9f78021ac63eea6441e58851fa95d36c900bacd8073937c9df29f48857a67066","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-21T20:19:24Z","title_canon_sha256":"63f54b09c4bab6724c911516753b300c23178ed93c4be1b2b203095e897f068f"},"schema_version":"1.0","source":{"id":"2211.11838","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.11838","created_at":"2026-07-05T06:21:29Z"},{"alias_kind":"arxiv_version","alias_value":"2211.11838v2","created_at":"2026-07-05T06:21:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.11838","created_at":"2026-07-05T06:21:29Z"},{"alias_kind":"pith_short_12","alias_value":"ULJ6JKB7IG3Y","created_at":"2026-07-05T06:21:29Z"},{"alias_kind":"pith_short_16","alias_value":"ULJ6JKB7IG3YDQJF","created_at":"2026-07-05T06:21:29Z"},{"alias_kind":"pith_short_8","alias_value":"ULJ6JKB7","created_at":"2026-07-05T06:21:29Z"}],"graph_snapshots":[{"event_id":"sha256:3f2f119c218a9202166876abd73371d534c6496a2ac5470445c4debcbe77e8f7","target":"graph","created_at":"2026-07-05T06:21:29Z","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/2211.11838/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Much recent work has been devoted to the problem of ensuring that a neural network's confidence scores match the true probability of being correct, i.e. the calibration problem. Of note, it was found that training with focal loss leads to better calibration than cross-entropy while achieving similar level of accuracy \\cite{mukhoti2020}. This success stems from focal loss regularizing the entropy of the model's prediction (controlled by the parameter $\\gamma$), thereby reining in the model's overconfidence. Further improvement is expected if $\\gamma$ is selected independently for each training ","authors_text":"Arindam Ghosh, Matthew R. Gormley, Thomas Schaaf","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-21T20:19:24Z","title":"AdaFocal: Calibration-aware Adaptive Focal Loss"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.11838","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":"sha256:8d68450d9cff34f112f9ec7c66493a44fb9f4af7ba8842648d3a4acff1bd1001","target":"record","created_at":"2026-07-05T06:21:29Z","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":"9f78021ac63eea6441e58851fa95d36c900bacd8073937c9df29f48857a67066","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-21T20:19:24Z","title_canon_sha256":"63f54b09c4bab6724c911516753b300c23178ed93c4be1b2b203095e897f068f"},"schema_version":"1.0","source":{"id":"2211.11838","kind":"arxiv","version":2}},"canonical_sha256":"a2d3e4a83f41b781c125f6394fe567749c0addd730e5facc9c181d347326e862","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a2d3e4a83f41b781c125f6394fe567749c0addd730e5facc9c181d347326e862","first_computed_at":"2026-07-05T06:21:29.743777Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:21:29.743777Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LeAyJKGieEzvS88e32qCEBFOuyFbtS9VihvY4sf9SHp2ni1On9EzFUm2eMem87U0gvwLK2KqiVV+DN9ZZXWuCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:21:29.744226Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.11838","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8d68450d9cff34f112f9ec7c66493a44fb9f4af7ba8842648d3a4acff1bd1001","sha256:3f2f119c218a9202166876abd73371d534c6496a2ac5470445c4debcbe77e8f7"],"state_sha256":"da0b51e81cf1505440c7e669e83b066514a83c4c0630444795b0c0b47470623b"}