{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:GPUXOWFZNDODGAYIP2O2RZXBJJ","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":"1cbec9051e6602a6aa007e3a3e6e3103d7591c512fd912827ffa868a2a05596e","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-19T16:33:42Z","title_canon_sha256":"2c07d8a3e448322a1e100999cf626ee359aca96eea737db05576ee4961015d9e"},"schema_version":"1.0","source":{"id":"2311.11367","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.11367","created_at":"2026-07-05T07:14:32Z"},{"alias_kind":"arxiv_version","alias_value":"2311.11367v1","created_at":"2026-07-05T07:14:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.11367","created_at":"2026-07-05T07:14:32Z"},{"alias_kind":"pith_short_12","alias_value":"GPUXOWFZNDOD","created_at":"2026-07-05T07:14:32Z"},{"alias_kind":"pith_short_16","alias_value":"GPUXOWFZNDODGAYI","created_at":"2026-07-05T07:14:32Z"},{"alias_kind":"pith_short_8","alias_value":"GPUXOWFZ","created_at":"2026-07-05T07:14:32Z"}],"graph_snapshots":[{"event_id":"sha256:d20298eb0812d7e409018721121d78c681b6cb72433297b5369f5d8674e2f45a","target":"graph","created_at":"2026-07-05T07:14:32Z","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/2311.11367/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Uncertainty quantification of deep neural networks has become an active field of research and plays a crucial role in various downstream tasks such as active learning. Recent advances in evidential deep learning shed light on the direct quantification of aleatoric and epistemic uncertainties with a single forward pass of the model. Most traditional approaches adopt an entropy-based method to derive evidential uncertainty in classification, quantifying uncertainty at the sample level. However, the variance-based method that has been widely applied in regression problems is seldom used in the cl","authors_text":"Brian Caffo, Craig Jones, Haris I. Sair, Harrison X. Bai, Ruxiao Duan","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-19T16:33:42Z","title":"Evidential Uncertainty Quantification: A Variance-Based Perspective"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.11367","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:a57fbd796f0491de5bcede02ad829597a52aee1ca2c770fd90fd30eace095879","target":"record","created_at":"2026-07-05T07:14:32Z","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":"1cbec9051e6602a6aa007e3a3e6e3103d7591c512fd912827ffa868a2a05596e","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-19T16:33:42Z","title_canon_sha256":"2c07d8a3e448322a1e100999cf626ee359aca96eea737db05576ee4961015d9e"},"schema_version":"1.0","source":{"id":"2311.11367","kind":"arxiv","version":1}},"canonical_sha256":"33e97758b968dc3303087e9da8e6e14a4cb81041958731641ac2aff5feec7bb8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"33e97758b968dc3303087e9da8e6e14a4cb81041958731641ac2aff5feec7bb8","first_computed_at":"2026-07-05T07:14:32.181839Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:14:32.181839Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eKFA6If5f4oy0s+FOGp3R62NIikqRx82O+ncMz9+yc0dsV2xdCDH2XbClB6pc2dclHH/AavK5F33XCHSAW3NCA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:14:32.182308Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.11367","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a57fbd796f0491de5bcede02ad829597a52aee1ca2c770fd90fd30eace095879","sha256:d20298eb0812d7e409018721121d78c681b6cb72433297b5369f5d8674e2f45a"],"state_sha256":"c6a3788d9a299d892ee1f065b944c1ff7b3109bb415a382c6af8bda5c0377f8a"}