{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:3BSH2X52AC5SKDAOWS2JKMVYTO","short_pith_number":"pith:3BSH2X52","canonical_record":{"source":{"id":"1904.12220","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-27T22:33:34Z","cross_cats_sorted":["cs.CV","stat.ML"],"title_canon_sha256":"e142cc1dfa224095c9b06e4f05e057cafe79e62d332a63f1d606bffa60aef5b0","abstract_canon_sha256":"1a169b7cc906559dc45a83058eb456a28cc4911eac8eede49767b2e910bf54a9"},"schema_version":"1.0"},"canonical_sha256":"d8647d5fba00bb250c0eb4b49532b89bab9c16b0a31977dc0fa890cca0ff72c2","source":{"kind":"arxiv","id":"1904.12220","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.12220","created_at":"2026-05-17T23:47:38Z"},{"alias_kind":"arxiv_version","alias_value":"1904.12220v1","created_at":"2026-05-17T23:47:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.12220","created_at":"2026-05-17T23:47:38Z"},{"alias_kind":"pith_short_12","alias_value":"3BSH2X52AC5S","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"3BSH2X52AC5SKDAO","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"3BSH2X52","created_at":"2026-05-18T12:33:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:3BSH2X52AC5SKDAOWS2JKMVYTO","target":"record","payload":{"canonical_record":{"source":{"id":"1904.12220","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-27T22:33:34Z","cross_cats_sorted":["cs.CV","stat.ML"],"title_canon_sha256":"e142cc1dfa224095c9b06e4f05e057cafe79e62d332a63f1d606bffa60aef5b0","abstract_canon_sha256":"1a169b7cc906559dc45a83058eb456a28cc4911eac8eede49767b2e910bf54a9"},"schema_version":"1.0"},"canonical_sha256":"d8647d5fba00bb250c0eb4b49532b89bab9c16b0a31977dc0fa890cca0ff72c2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:47:38.633929Z","signature_b64":"57fRl8EmsJx+WUN6ZCqYewvK1WOGA1H4xn5WPdbTSKl9PwP/34eZkBkzXCogpbpWbHmeULxD1ehQ4Z8pjD0SAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d8647d5fba00bb250c0eb4b49532b89bab9c16b0a31977dc0fa890cca0ff72c2","last_reissued_at":"2026-05-17T23:47:38.633499Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:47:38.633499Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.12220","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:47:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mmEc8tyWSqSYmSHtrhvNXZ3wiys/fjPgyWto7itEV3xLsXImZHh8hYqtPjGhsGRAto2UAts0Yxkq89BKK9V0Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T22:45:33.008906Z"},"content_sha256":"29e014b75baab8d4e387b73097d7db01368088fedbf9ee4c9d73cfdfa25c8533","schema_version":"1.0","event_id":"sha256:29e014b75baab8d4e387b73097d7db01368088fedbf9ee4c9d73cfdfa25c8533"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:3BSH2X52AC5SKDAOWS2JKMVYTO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Analysis of Confident-Classifiers for Out-of-distribution Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","stat.ML"],"primary_cat":"cs.LG","authors_text":"Ashish Gaurav, Buu Phan, Krzysztof Czarnecki, Rick Salay, Sachin Vernekar, Taylor Denouden, Vahdat Abdelzad","submitted_at":"2019-04-27T22:33:34Z","abstract_excerpt":"Discriminatively trained neural classifiers can be trusted, only when the input data comes from the training distribution (in-distribution). Therefore, detecting out-of-distribution (OOD) samples is very important to avoid classification errors. In the context of OOD detection for image classification, one of the recent approaches proposes training a classifier called \"confident-classifier\" by minimizing the standard cross-entropy loss on in-distribution samples and minimizing the KL divergence between the predictive distribution of OOD samples in the low-density regions of in-distribution and"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.12220","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:47:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w9GEgucyk+nGbY4MTe+NBjemPrQhRfRYWv/M6YVtIRTRB8zSweY88mFrvSwgMkWJeNtA0A0QTT8RIqCwWe7UDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T22:45:33.009692Z"},"content_sha256":"29dde8c6847c90c06b28ad5e5b9f5fc1a144c63a890727f3dc4252c51c2014d2","schema_version":"1.0","event_id":"sha256:29dde8c6847c90c06b28ad5e5b9f5fc1a144c63a890727f3dc4252c51c2014d2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3BSH2X52AC5SKDAOWS2JKMVYTO/bundle.json","state_url":"https://pith.science/pith/3BSH2X52AC5SKDAOWS2JKMVYTO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3BSH2X52AC5SKDAOWS2JKMVYTO/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-29T22:45:33Z","links":{"resolver":"https://pith.science/pith/3BSH2X52AC5SKDAOWS2JKMVYTO","bundle":"https://pith.science/pith/3BSH2X52AC5SKDAOWS2JKMVYTO/bundle.json","state":"https://pith.science/pith/3BSH2X52AC5SKDAOWS2JKMVYTO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3BSH2X52AC5SKDAOWS2JKMVYTO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:3BSH2X52AC5SKDAOWS2JKMVYTO","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":"1a169b7cc906559dc45a83058eb456a28cc4911eac8eede49767b2e910bf54a9","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-27T22:33:34Z","title_canon_sha256":"e142cc1dfa224095c9b06e4f05e057cafe79e62d332a63f1d606bffa60aef5b0"},"schema_version":"1.0","source":{"id":"1904.12220","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.12220","created_at":"2026-05-17T23:47:38Z"},{"alias_kind":"arxiv_version","alias_value":"1904.12220v1","created_at":"2026-05-17T23:47:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.12220","created_at":"2026-05-17T23:47:38Z"},{"alias_kind":"pith_short_12","alias_value":"3BSH2X52AC5S","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"3BSH2X52AC5SKDAO","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"3BSH2X52","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:29dde8c6847c90c06b28ad5e5b9f5fc1a144c63a890727f3dc4252c51c2014d2","target":"graph","created_at":"2026-05-17T23:47:38Z","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"},"paper":{"abstract_excerpt":"Discriminatively trained neural classifiers can be trusted, only when the input data comes from the training distribution (in-distribution). Therefore, detecting out-of-distribution (OOD) samples is very important to avoid classification errors. In the context of OOD detection for image classification, one of the recent approaches proposes training a classifier called \"confident-classifier\" by minimizing the standard cross-entropy loss on in-distribution samples and minimizing the KL divergence between the predictive distribution of OOD samples in the low-density regions of in-distribution and","authors_text":"Ashish Gaurav, Buu Phan, Krzysztof Czarnecki, Rick Salay, Sachin Vernekar, Taylor Denouden, Vahdat Abdelzad","cross_cats":["cs.CV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-27T22:33:34Z","title":"Analysis of Confident-Classifiers for Out-of-distribution Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.12220","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":"sha256:29e014b75baab8d4e387b73097d7db01368088fedbf9ee4c9d73cfdfa25c8533","target":"record","created_at":"2026-05-17T23:47:38Z","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":"1a169b7cc906559dc45a83058eb456a28cc4911eac8eede49767b2e910bf54a9","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-27T22:33:34Z","title_canon_sha256":"e142cc1dfa224095c9b06e4f05e057cafe79e62d332a63f1d606bffa60aef5b0"},"schema_version":"1.0","source":{"id":"1904.12220","kind":"arxiv","version":1}},"canonical_sha256":"d8647d5fba00bb250c0eb4b49532b89bab9c16b0a31977dc0fa890cca0ff72c2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d8647d5fba00bb250c0eb4b49532b89bab9c16b0a31977dc0fa890cca0ff72c2","first_computed_at":"2026-05-17T23:47:38.633499Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:47:38.633499Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"57fRl8EmsJx+WUN6ZCqYewvK1WOGA1H4xn5WPdbTSKl9PwP/34eZkBkzXCogpbpWbHmeULxD1ehQ4Z8pjD0SAg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:47:38.633929Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.12220","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:29e014b75baab8d4e387b73097d7db01368088fedbf9ee4c9d73cfdfa25c8533","sha256:29dde8c6847c90c06b28ad5e5b9f5fc1a144c63a890727f3dc4252c51c2014d2"],"state_sha256":"66a7119ea9faac64128c6e0b3163e6a2b3e89007965730daebd750a0f22527f9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0bWVgCma+UrRln4dA2fck+NMcIBDq1mKpANRbpBcfBaztLE3W6U2H6gL1H5NhrzSP4VDU2R3dtnsmxM/9jhoCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-29T22:45:33.013733Z","bundle_sha256":"74cc1c4060ecca7c4f8c0c108d0fa873f5fe74886d69862a5a1c6ac125fd37ce"}}