{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:GEOTSSGIF4XEUHG24VZ5ZT45XW","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":"ff9ad23676630fd13910fd817fdd05ed4ff919138a6db70f99107811f1e48bcc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-10-21T07:16:09Z","title_canon_sha256":"970af0c0f9f2cf5f46351e873edb860d03a7a081ca20532e9d5d3524330f38da"},"schema_version":"1.0","source":{"id":"2310.13923","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.13923","created_at":"2026-07-05T07:05:14Z"},{"alias_kind":"arxiv_version","alias_value":"2310.13923v2","created_at":"2026-07-05T07:05:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.13923","created_at":"2026-07-05T07:05:14Z"},{"alias_kind":"pith_short_12","alias_value":"GEOTSSGIF4XE","created_at":"2026-07-05T07:05:14Z"},{"alias_kind":"pith_short_16","alias_value":"GEOTSSGIF4XEUHG2","created_at":"2026-07-05T07:05:14Z"},{"alias_kind":"pith_short_8","alias_value":"GEOTSSGI","created_at":"2026-07-05T07:05:14Z"}],"graph_snapshots":[{"event_id":"sha256:940653608599d51c13cc4bc4e3103574075a0cd4afc2ad7be1cfdbdc737f4d1d","target":"graph","created_at":"2026-07-05T07:05:14Z","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/2310.13923/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Out-of-distribution (OOD) detection is important for deploying reliable machine learning models on real-world applications. Recent advances in outlier exposure have shown promising results on OOD detection via fine-tuning model with informatively sampled auxiliary outliers. However, previous methods assume that the collected outliers can be sufficiently large and representative to cover the boundary between ID and OOD data, which might be impractical and challenging. In this work, we propose a novel framework, namely, Diversified Outlier Exposure (DivOE), for effective OOD detection via inform","authors_text":"Bo Han, Gang Niu, Geng Yu, Jiangchao Yao, Jianing Zhu, Masashi Sugiyama, Tongliang Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-10-21T07:16:09Z","title":"Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.13923","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:c2242a3b2e30c13a5dadfad2e26db702e79f1c4a0effe005119475d354733759","target":"record","created_at":"2026-07-05T07:05:14Z","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":"ff9ad23676630fd13910fd817fdd05ed4ff919138a6db70f99107811f1e48bcc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-10-21T07:16:09Z","title_canon_sha256":"970af0c0f9f2cf5f46351e873edb860d03a7a081ca20532e9d5d3524330f38da"},"schema_version":"1.0","source":{"id":"2310.13923","kind":"arxiv","version":2}},"canonical_sha256":"311d3948c82f2e4a1cdae573dccf9dbda98ce0aab0a30490f051a142cfbc878b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"311d3948c82f2e4a1cdae573dccf9dbda98ce0aab0a30490f051a142cfbc878b","first_computed_at":"2026-07-05T07:05:14.178208Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:05:14.178208Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jYrmboOrrMs5Ub3dIz7DOOzCIVf/TyRp+LJVbgSo1GkheizkNkMWEYaElrsHgI7XatcGCTfqLQMwc6aOpcLICA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:05:14.178687Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.13923","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c2242a3b2e30c13a5dadfad2e26db702e79f1c4a0effe005119475d354733759","sha256:940653608599d51c13cc4bc4e3103574075a0cd4afc2ad7be1cfdbdc737f4d1d"],"state_sha256":"e81b077f351da33f80eab22fcfb5f9ccb542c8da0bc657542747b336418446ef"}