{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:EEW5EYQGL2JB32DZKJ2G5MR53K","short_pith_number":"pith:EEW5EYQG","canonical_record":{"source":{"id":"2010.12905","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-24T14:05:03Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"9d6484f6a5a272a1a63dd1b8a3bbe1119100c89b9614f0dfc2c3a97691384649","abstract_canon_sha256":"e4c22dfc47eb108ba88c6f5ae130f5e7aac706041995e84287c2da2e038daeb4"},"schema_version":"1.0"},"canonical_sha256":"212dd262065e921de87952746eb23ddabd2b261b3787e13bfb3efb689ebdc52b","source":{"kind":"arxiv","id":"2010.12905","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.12905","created_at":"2026-07-05T01:45:49Z"},{"alias_kind":"arxiv_version","alias_value":"2010.12905v1","created_at":"2026-07-05T01:45:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.12905","created_at":"2026-07-05T01:45:49Z"},{"alias_kind":"pith_short_12","alias_value":"EEW5EYQGL2JB","created_at":"2026-07-05T01:45:49Z"},{"alias_kind":"pith_short_16","alias_value":"EEW5EYQGL2JB32DZ","created_at":"2026-07-05T01:45:49Z"},{"alias_kind":"pith_short_8","alias_value":"EEW5EYQG","created_at":"2026-07-05T01:45:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:EEW5EYQGL2JB32DZKJ2G5MR53K","target":"record","payload":{"canonical_record":{"source":{"id":"2010.12905","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-24T14:05:03Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"9d6484f6a5a272a1a63dd1b8a3bbe1119100c89b9614f0dfc2c3a97691384649","abstract_canon_sha256":"e4c22dfc47eb108ba88c6f5ae130f5e7aac706041995e84287c2da2e038daeb4"},"schema_version":"1.0"},"canonical_sha256":"212dd262065e921de87952746eb23ddabd2b261b3787e13bfb3efb689ebdc52b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:45:49.568158Z","signature_b64":"An32O5ZbJgYdy9vo3ANfw8jQtCVUToSppvOEnk9q51tQdPIlD0qy4D0mc7hS1vaSqoOFQGZBpd+or5vYK1h/DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"212dd262065e921de87952746eb23ddabd2b261b3787e13bfb3efb689ebdc52b","last_reissued_at":"2026-07-05T01:45:49.567751Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:45:49.567751Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.12905","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":"2026-07-05T01:45:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9n6SHVCn6k/LtaxX8QugAQb0jtmbUXH/RicvwbEbKsd0L9Yu2/2z/RdrZ3rMHYB0uDamvP3FdVHch+LzwUWlAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-15T20:49:21.009155Z"},"content_sha256":"01f04e3c091d46e5cc2714d40723e97d69b1e065d7cd5b578bee79ca6b69af06","schema_version":"1.0","event_id":"sha256:01f04e3c091d46e5cc2714d40723e97d69b1e065d7cd5b578bee79ca6b69af06"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:EEW5EYQGL2JB32DZKJ2G5MR53K","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ATRO: Adversarial Training with a Rejection Option","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Masahiro Kato, Yoshihiro Fukuhara, Zhenghang Cui","submitted_at":"2020-10-24T14:05:03Z","abstract_excerpt":"This paper proposes a classification framework with a rejection option to mitigate the performance deterioration caused by adversarial examples. While recent machine learning algorithms achieve high prediction performance, they are empirically vulnerable to adversarial examples, which are slightly perturbed data samples that are wrongly classified. In real-world applications, adversarial attacks using such adversarial examples could cause serious problems. To this end, various methods are proposed to obtain a classifier that is robust against adversarial examples. Adversarial training is one o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.12905","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2010.12905/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T01:45:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lixOn+NnbjD1KldsvIlrPdsPVAdgh14Va3K5qZyCYQEhpVFr9JCXRqLy1RYcbSS2u0YTbsWm+mkY/FJxPpY/AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-15T20:49:21.009552Z"},"content_sha256":"7e08d85dfec15d40b0d432aac398109e72b82d57878fd7d2d110ddf548db2bbc","schema_version":"1.0","event_id":"sha256:7e08d85dfec15d40b0d432aac398109e72b82d57878fd7d2d110ddf548db2bbc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EEW5EYQGL2JB32DZKJ2G5MR53K/bundle.json","state_url":"https://pith.science/pith/EEW5EYQGL2JB32DZKJ2G5MR53K/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EEW5EYQGL2JB32DZKJ2G5MR53K/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":"2026-07-15T20:49:21Z","links":{"resolver":"https://pith.science/pith/EEW5EYQGL2JB32DZKJ2G5MR53K","bundle":"https://pith.science/pith/EEW5EYQGL2JB32DZKJ2G5MR53K/bundle.json","state":"https://pith.science/pith/EEW5EYQGL2JB32DZKJ2G5MR53K/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EEW5EYQGL2JB32DZKJ2G5MR53K/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:EEW5EYQGL2JB32DZKJ2G5MR53K","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":"e4c22dfc47eb108ba88c6f5ae130f5e7aac706041995e84287c2da2e038daeb4","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-24T14:05:03Z","title_canon_sha256":"9d6484f6a5a272a1a63dd1b8a3bbe1119100c89b9614f0dfc2c3a97691384649"},"schema_version":"1.0","source":{"id":"2010.12905","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.12905","created_at":"2026-07-05T01:45:49Z"},{"alias_kind":"arxiv_version","alias_value":"2010.12905v1","created_at":"2026-07-05T01:45:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.12905","created_at":"2026-07-05T01:45:49Z"},{"alias_kind":"pith_short_12","alias_value":"EEW5EYQGL2JB","created_at":"2026-07-05T01:45:49Z"},{"alias_kind":"pith_short_16","alias_value":"EEW5EYQGL2JB32DZ","created_at":"2026-07-05T01:45:49Z"},{"alias_kind":"pith_short_8","alias_value":"EEW5EYQG","created_at":"2026-07-05T01:45:49Z"}],"graph_snapshots":[{"event_id":"sha256:7e08d85dfec15d40b0d432aac398109e72b82d57878fd7d2d110ddf548db2bbc","target":"graph","created_at":"2026-07-05T01:45:49Z","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/2010.12905/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper proposes a classification framework with a rejection option to mitigate the performance deterioration caused by adversarial examples. While recent machine learning algorithms achieve high prediction performance, they are empirically vulnerable to adversarial examples, which are slightly perturbed data samples that are wrongly classified. In real-world applications, adversarial attacks using such adversarial examples could cause serious problems. To this end, various methods are proposed to obtain a classifier that is robust against adversarial examples. Adversarial training is one o","authors_text":"Masahiro Kato, Yoshihiro Fukuhara, Zhenghang Cui","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-24T14:05:03Z","title":"ATRO: Adversarial Training with a Rejection Option"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.12905","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":"sha256:01f04e3c091d46e5cc2714d40723e97d69b1e065d7cd5b578bee79ca6b69af06","target":"record","created_at":"2026-07-05T01:45:49Z","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":"e4c22dfc47eb108ba88c6f5ae130f5e7aac706041995e84287c2da2e038daeb4","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-24T14:05:03Z","title_canon_sha256":"9d6484f6a5a272a1a63dd1b8a3bbe1119100c89b9614f0dfc2c3a97691384649"},"schema_version":"1.0","source":{"id":"2010.12905","kind":"arxiv","version":1}},"canonical_sha256":"212dd262065e921de87952746eb23ddabd2b261b3787e13bfb3efb689ebdc52b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"212dd262065e921de87952746eb23ddabd2b261b3787e13bfb3efb689ebdc52b","first_computed_at":"2026-07-05T01:45:49.567751Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:45:49.567751Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"An32O5ZbJgYdy9vo3ANfw8jQtCVUToSppvOEnk9q51tQdPIlD0qy4D0mc7hS1vaSqoOFQGZBpd+or5vYK1h/DQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:45:49.568158Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.12905","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:01f04e3c091d46e5cc2714d40723e97d69b1e065d7cd5b578bee79ca6b69af06","sha256:7e08d85dfec15d40b0d432aac398109e72b82d57878fd7d2d110ddf548db2bbc"],"state_sha256":"e112a4841b384b43f752e8872c905587b3af9c6306dcb4709f79720d8ec8808b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ML+vVi26cLeDtHoM0XlzxtxF3kwBaVHOK6w9e2HlarTLNV6vz1RwJwMORke4VTMYeKKVaEPH1Ow2AxReRkXbAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-15T20:49:21.011703Z","bundle_sha256":"473955143b7c8594768ed900402073c421da797f54eaecac86437c0c07145c05"}}