{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:FCDJLAAZ3UQ24NLPEOVVRD4ZZK","short_pith_number":"pith:FCDJLAAZ","canonical_record":{"source":{"id":"2002.12718","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-02-28T14:03:31Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"15781ecdfa98871a8281c63f647501dbd98de4ebc7d9fd2256fcdbc0675d5c98","abstract_canon_sha256":"62aeb23657c28bd22594f30a7888f60a32c6d40f2dc94ba4e78b9da7beff9ac2"},"schema_version":"1.0"},"canonical_sha256":"2886958019dd21ae356f23ab588f99caaf0e178255619d7aa490bc208b4a1b02","source":{"kind":"arxiv","id":"2002.12718","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.12718","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"arxiv_version","alias_value":"2002.12718v2","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.12718","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"pith_short_12","alias_value":"FCDJLAAZ3UQ2","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"pith_short_16","alias_value":"FCDJLAAZ3UQ24NLP","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"pith_short_8","alias_value":"FCDJLAAZ","created_at":"2026-07-05T01:27:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:FCDJLAAZ3UQ24NLPEOVVRD4ZZK","target":"record","payload":{"canonical_record":{"source":{"id":"2002.12718","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-02-28T14:03:31Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"15781ecdfa98871a8281c63f647501dbd98de4ebc7d9fd2256fcdbc0675d5c98","abstract_canon_sha256":"62aeb23657c28bd22594f30a7888f60a32c6d40f2dc94ba4e78b9da7beff9ac2"},"schema_version":"1.0"},"canonical_sha256":"2886958019dd21ae356f23ab588f99caaf0e178255619d7aa490bc208b4a1b02","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:27:21.558279Z","signature_b64":"VGEKdxO7LDWgARYOrLL3DhK2l7mkGiHfqlrNz5YbvOyh1BtUSdEBPcyqX6xDb6je6JvZDkBW23vpQp4F8pNVCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2886958019dd21ae356f23ab588f99caaf0e178255619d7aa490bc208b4a1b02","last_reissued_at":"2026-07-05T01:27:21.557852Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:27:21.557852Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2002.12718","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:27:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5EirAROsAflk4AYR5pfPBLDw+p94xAzNwVzaTO2QPGF82Pmnxy1MdWiMCyLtyUSay2rUn8M6zratvq/0Y5QbBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T13:51:12.098886Z"},"content_sha256":"79f173ce9bdca0a07c93e6af98abf9970b9307e2deeac2e495eddf6b8cce3870","schema_version":"1.0","event_id":"sha256:79f173ce9bdca0a07c93e6af98abf9970b9307e2deeac2e495eddf6b8cce3870"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:FCDJLAAZ3UQ24NLPEOVVRD4ZZK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DROCC: Deep Robust One-Class Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Aditi Raghunathan, Harsha Vardhan Simhadri, Moksh Jain, Prateek Jain, Sachin Goyal","submitted_at":"2020-02-28T14:03:31Z","abstract_excerpt":"Classical approaches for one-class problems such as one-class SVM and isolation forest require careful feature engineering when applied to structured domains like images. State-of-the-art methods aim to leverage deep learning to learn appropriate features via two main approaches. The first approach based on predicting transformations (Golan & El-Yaniv, 2018; Hendrycks et al., 2019a) while successful in some domains, crucially depends on an appropriate domain-specific set of transformations that are hard to obtain in general. The second approach of minimizing a classical one-class loss on the l"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.12718","kind":"arxiv","version":2},"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/2002.12718/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":"2026-07-05T01:27:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Tcg6rkfa06vcqqNVSRTsG/7ZK3PZgSWdbF4/MoTPy6oqBSDadCZZBaKctSWt6LrfDzrohZWivwIEjxjslc8oBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T13:51:12.099256Z"},"content_sha256":"0006c7a7d5f9271b531218cae2f61236c30378666cfdb82441c365f3a32e61f1","schema_version":"1.0","event_id":"sha256:0006c7a7d5f9271b531218cae2f61236c30378666cfdb82441c365f3a32e61f1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FCDJLAAZ3UQ24NLPEOVVRD4ZZK/bundle.json","state_url":"https://pith.science/pith/FCDJLAAZ3UQ24NLPEOVVRD4ZZK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FCDJLAAZ3UQ24NLPEOVVRD4ZZK/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":"2026-07-06T13:51:12Z","links":{"resolver":"https://pith.science/pith/FCDJLAAZ3UQ24NLPEOVVRD4ZZK","bundle":"https://pith.science/pith/FCDJLAAZ3UQ24NLPEOVVRD4ZZK/bundle.json","state":"https://pith.science/pith/FCDJLAAZ3UQ24NLPEOVVRD4ZZK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FCDJLAAZ3UQ24NLPEOVVRD4ZZK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:FCDJLAAZ3UQ24NLPEOVVRD4ZZK","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":"62aeb23657c28bd22594f30a7888f60a32c6d40f2dc94ba4e78b9da7beff9ac2","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-02-28T14:03:31Z","title_canon_sha256":"15781ecdfa98871a8281c63f647501dbd98de4ebc7d9fd2256fcdbc0675d5c98"},"schema_version":"1.0","source":{"id":"2002.12718","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.12718","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"arxiv_version","alias_value":"2002.12718v2","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.12718","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"pith_short_12","alias_value":"FCDJLAAZ3UQ2","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"pith_short_16","alias_value":"FCDJLAAZ3UQ24NLP","created_at":"2026-07-05T01:27:21Z"},{"alias_kind":"pith_short_8","alias_value":"FCDJLAAZ","created_at":"2026-07-05T01:27:21Z"}],"graph_snapshots":[{"event_id":"sha256:0006c7a7d5f9271b531218cae2f61236c30378666cfdb82441c365f3a32e61f1","target":"graph","created_at":"2026-07-05T01:27:21Z","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/2002.12718/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Classical approaches for one-class problems such as one-class SVM and isolation forest require careful feature engineering when applied to structured domains like images. State-of-the-art methods aim to leverage deep learning to learn appropriate features via two main approaches. The first approach based on predicting transformations (Golan & El-Yaniv, 2018; Hendrycks et al., 2019a) while successful in some domains, crucially depends on an appropriate domain-specific set of transformations that are hard to obtain in general. The second approach of minimizing a classical one-class loss on the l","authors_text":"Aditi Raghunathan, Harsha Vardhan Simhadri, Moksh Jain, Prateek Jain, Sachin Goyal","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-02-28T14:03:31Z","title":"DROCC: Deep Robust One-Class Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.12718","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":"sha256:79f173ce9bdca0a07c93e6af98abf9970b9307e2deeac2e495eddf6b8cce3870","target":"record","created_at":"2026-07-05T01:27:21Z","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":"62aeb23657c28bd22594f30a7888f60a32c6d40f2dc94ba4e78b9da7beff9ac2","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-02-28T14:03:31Z","title_canon_sha256":"15781ecdfa98871a8281c63f647501dbd98de4ebc7d9fd2256fcdbc0675d5c98"},"schema_version":"1.0","source":{"id":"2002.12718","kind":"arxiv","version":2}},"canonical_sha256":"2886958019dd21ae356f23ab588f99caaf0e178255619d7aa490bc208b4a1b02","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2886958019dd21ae356f23ab588f99caaf0e178255619d7aa490bc208b4a1b02","first_computed_at":"2026-07-05T01:27:21.557852Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:27:21.557852Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VGEKdxO7LDWgARYOrLL3DhK2l7mkGiHfqlrNz5YbvOyh1BtUSdEBPcyqX6xDb6je6JvZDkBW23vpQp4F8pNVCA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:27:21.558279Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.12718","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:79f173ce9bdca0a07c93e6af98abf9970b9307e2deeac2e495eddf6b8cce3870","sha256:0006c7a7d5f9271b531218cae2f61236c30378666cfdb82441c365f3a32e61f1"],"state_sha256":"fd7c88c662314a11b6367ea63e7a5d520d4264f3ec6b087911dc3e97bd1910af"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mmLpfOKZl2HgNBKl8QBLE3VQCNkZYGXvwJVAu/Sn44j6SiSKxeR2YT40YjGUCdnOcbuGotzCfddod8k+FCrkAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T13:51:12.101247Z","bundle_sha256":"34c0cae7f1214fa46ddcacaff0970f3034cbd393f3e8d8fc95966a3eda155816"}}