{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:2YJD4IVXK7WFTB2INT4RXMN4YB","short_pith_number":"pith:2YJD4IVX","canonical_record":{"source":{"id":"1802.04865","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-13T21:31:36Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"43db7dad01bda6e598952dc0d2495a426844e5fafc47a24361b4a5178f2d06f1","abstract_canon_sha256":"8c2357c373f0cfa977c52edd19b4c879e4eeefe7fd2fdd19bb2e9eb8acbf93ba"},"schema_version":"1.0"},"canonical_sha256":"d6123e22b757ec5987486cf91bb1bcc05253379b897e58a22fe6459558b0c71f","source":{"kind":"arxiv","id":"1802.04865","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.04865","created_at":"2026-05-18T00:23:22Z"},{"alias_kind":"arxiv_version","alias_value":"1802.04865v1","created_at":"2026-05-18T00:23:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.04865","created_at":"2026-05-18T00:23:22Z"},{"alias_kind":"pith_short_12","alias_value":"2YJD4IVXK7WF","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"2YJD4IVXK7WFTB2I","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"2YJD4IVX","created_at":"2026-05-18T12:32:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:2YJD4IVXK7WFTB2INT4RXMN4YB","target":"record","payload":{"canonical_record":{"source":{"id":"1802.04865","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-13T21:31:36Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"43db7dad01bda6e598952dc0d2495a426844e5fafc47a24361b4a5178f2d06f1","abstract_canon_sha256":"8c2357c373f0cfa977c52edd19b4c879e4eeefe7fd2fdd19bb2e9eb8acbf93ba"},"schema_version":"1.0"},"canonical_sha256":"d6123e22b757ec5987486cf91bb1bcc05253379b897e58a22fe6459558b0c71f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:23:22.396602Z","signature_b64":"Jlf9GxOeeyki1LjQTf3bXKm5p0XbLvQA97gtP1uggCMrhcjafT8PalAYRkYieGkAjBBE2rkGjoQgDPdb81zKAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d6123e22b757ec5987486cf91bb1bcc05253379b897e58a22fe6459558b0c71f","last_reissued_at":"2026-05-18T00:23:22.395900Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:23:22.395900Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.04865","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":"2026-05-18T00:23:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E5omPVQnO58Sac2nyZVxR12LqSBZQZBspMb65qaI/hEKvIpmPOFGAWQZl3zqsb5XiWw5S1Rn/hlGx8X7KAMlCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T06:12:53.942841Z"},"content_sha256":"64e1f1087ada9c35bf8889bffff55cf68fb103dac2026bb38e6d8cfd06b6ea51","schema_version":"1.0","event_id":"sha256:64e1f1087ada9c35bf8889bffff55cf68fb103dac2026bb38e6d8cfd06b6ea51"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:2YJD4IVXK7WFTB2INT4RXMN4YB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Confidence for Out-of-Distribution Detection in Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Graham W. Taylor, Terrance DeVries","submitted_at":"2018-02-13T21:31:36Z","abstract_excerpt":"Modern neural networks are very powerful predictive models, but they are often incapable of recognizing when their predictions may be wrong. Closely related to this is the task of out-of-distribution detection, where a network must determine whether or not an input is outside of the set on which it is expected to safely perform. To jointly address these issues, we propose a method of learning confidence estimates for neural networks that is simple to implement and produces intuitively interpretable outputs. We demonstrate that on the task of out-of-distribution detection, our technique surpass"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.04865","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":"2026-05-18T00:23:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kwUsFVXond2dnowIzDQIGbv5ym8ZsXKW3w3+Xo2bG4nfR8lgn4ekat88aUhvmze31qYsoSziozdMXgQS/Lv0Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T06:12:53.943193Z"},"content_sha256":"24b41cb4e96f59c590b06329ebf6169e69a7362ca3a25d3b1ab75cf88c18841f","schema_version":"1.0","event_id":"sha256:24b41cb4e96f59c590b06329ebf6169e69a7362ca3a25d3b1ab75cf88c18841f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2YJD4IVXK7WFTB2INT4RXMN4YB/bundle.json","state_url":"https://pith.science/pith/2YJD4IVXK7WFTB2INT4RXMN4YB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2YJD4IVXK7WFTB2INT4RXMN4YB/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":"2026-05-28T06:12:53Z","links":{"resolver":"https://pith.science/pith/2YJD4IVXK7WFTB2INT4RXMN4YB","bundle":"https://pith.science/pith/2YJD4IVXK7WFTB2INT4RXMN4YB/bundle.json","state":"https://pith.science/pith/2YJD4IVXK7WFTB2INT4RXMN4YB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2YJD4IVXK7WFTB2INT4RXMN4YB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:2YJD4IVXK7WFTB2INT4RXMN4YB","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":"8c2357c373f0cfa977c52edd19b4c879e4eeefe7fd2fdd19bb2e9eb8acbf93ba","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-13T21:31:36Z","title_canon_sha256":"43db7dad01bda6e598952dc0d2495a426844e5fafc47a24361b4a5178f2d06f1"},"schema_version":"1.0","source":{"id":"1802.04865","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.04865","created_at":"2026-05-18T00:23:22Z"},{"alias_kind":"arxiv_version","alias_value":"1802.04865v1","created_at":"2026-05-18T00:23:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.04865","created_at":"2026-05-18T00:23:22Z"},{"alias_kind":"pith_short_12","alias_value":"2YJD4IVXK7WF","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"2YJD4IVXK7WFTB2I","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"2YJD4IVX","created_at":"2026-05-18T12:32:02Z"}],"graph_snapshots":[{"event_id":"sha256:24b41cb4e96f59c590b06329ebf6169e69a7362ca3a25d3b1ab75cf88c18841f","target":"graph","created_at":"2026-05-18T00:23:22Z","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":"Modern neural networks are very powerful predictive models, but they are often incapable of recognizing when their predictions may be wrong. Closely related to this is the task of out-of-distribution detection, where a network must determine whether or not an input is outside of the set on which it is expected to safely perform. To jointly address these issues, we propose a method of learning confidence estimates for neural networks that is simple to implement and produces intuitively interpretable outputs. We demonstrate that on the task of out-of-distribution detection, our technique surpass","authors_text":"Graham W. Taylor, Terrance DeVries","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-13T21:31:36Z","title":"Learning Confidence for Out-of-Distribution Detection in Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.04865","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":"sha256:64e1f1087ada9c35bf8889bffff55cf68fb103dac2026bb38e6d8cfd06b6ea51","target":"record","created_at":"2026-05-18T00:23:22Z","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":"8c2357c373f0cfa977c52edd19b4c879e4eeefe7fd2fdd19bb2e9eb8acbf93ba","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-13T21:31:36Z","title_canon_sha256":"43db7dad01bda6e598952dc0d2495a426844e5fafc47a24361b4a5178f2d06f1"},"schema_version":"1.0","source":{"id":"1802.04865","kind":"arxiv","version":1}},"canonical_sha256":"d6123e22b757ec5987486cf91bb1bcc05253379b897e58a22fe6459558b0c71f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d6123e22b757ec5987486cf91bb1bcc05253379b897e58a22fe6459558b0c71f","first_computed_at":"2026-05-18T00:23:22.395900Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:23:22.395900Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Jlf9GxOeeyki1LjQTf3bXKm5p0XbLvQA97gtP1uggCMrhcjafT8PalAYRkYieGkAjBBE2rkGjoQgDPdb81zKAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:23:22.396602Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.04865","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:64e1f1087ada9c35bf8889bffff55cf68fb103dac2026bb38e6d8cfd06b6ea51","sha256:24b41cb4e96f59c590b06329ebf6169e69a7362ca3a25d3b1ab75cf88c18841f"],"state_sha256":"301271f19f7de44961526ce96630db8e5bbe992d9a69f4b1b05ee0801d62affe"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gdSmjCF3HReDzJqCzDYPh3pHiMLlzXKGroRGo2zBRtEuegEMSgiloUjAqV5xupuPD+uuYi9Z4Wicdr8TC/zGBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T06:12:53.945253Z","bundle_sha256":"764cca8628ef9b0bc98f8b51cda54f785cc054ec0ad334aa5fc61d9e307acda5"}}