{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:XLMG72LSZD7RJQALAOCO2GPWTS","short_pith_number":"pith:XLMG72LS","canonical_record":{"source":{"id":"2312.02200","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-02T19:33:42Z","cross_cats_sorted":["cs.AI","stat.AP"],"title_canon_sha256":"ea3db9bfc156f2aa24cbbbfaa5aff673fbc8ead1f00665facfd9482448bd12cc","abstract_canon_sha256":"5a5541549618b21fdf2990c33a20d36d4ecec448638675741f5b5e53c0db0cb8"},"schema_version":"1.0"},"canonical_sha256":"bad86fe972c8ff14c00b0384ed19f69c849303226ccd4091d2bc0b5afc3c308c","source":{"kind":"arxiv","id":"2312.02200","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.02200","created_at":"2026-07-05T07:20:14Z"},{"alias_kind":"arxiv_version","alias_value":"2312.02200v1","created_at":"2026-07-05T07:20:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.02200","created_at":"2026-07-05T07:20:14Z"},{"alias_kind":"pith_short_12","alias_value":"XLMG72LSZD7R","created_at":"2026-07-05T07:20:14Z"},{"alias_kind":"pith_short_16","alias_value":"XLMG72LSZD7RJQAL","created_at":"2026-07-05T07:20:14Z"},{"alias_kind":"pith_short_8","alias_value":"XLMG72LS","created_at":"2026-07-05T07:20:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:XLMG72LSZD7RJQALAOCO2GPWTS","target":"record","payload":{"canonical_record":{"source":{"id":"2312.02200","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-02T19:33:42Z","cross_cats_sorted":["cs.AI","stat.AP"],"title_canon_sha256":"ea3db9bfc156f2aa24cbbbfaa5aff673fbc8ead1f00665facfd9482448bd12cc","abstract_canon_sha256":"5a5541549618b21fdf2990c33a20d36d4ecec448638675741f5b5e53c0db0cb8"},"schema_version":"1.0"},"canonical_sha256":"bad86fe972c8ff14c00b0384ed19f69c849303226ccd4091d2bc0b5afc3c308c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:20:14.270405Z","signature_b64":"D8M+wGZWJ6hoBRuNV74aHkpmuIqS8PtItb9awoXxzooyERmvRlm+oLbPIXlFXNr0Ex2WHRphfcd/mW9i1I7ZDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bad86fe972c8ff14c00b0384ed19f69c849303226ccd4091d2bc0b5afc3c308c","last_reissued_at":"2026-07-05T07:20:14.269901Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:20:14.269901Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.02200","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":"2026-07-05T07:20:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gljnZIpZbitJ/lP+U6GlDcZc8u15IktY1/bHr6s1bRpnL99Jt2FzUdDmrkepBPDc4bVlVZW+a95N8y/16Q0jAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T04:14:14.942100Z"},"content_sha256":"7ac2ed9a465af0e431144fcfa3eb28831316571da058cd7827d6aebaace7a1cd","schema_version":"1.0","event_id":"sha256:7ac2ed9a465af0e431144fcfa3eb28831316571da058cd7827d6aebaace7a1cd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:XLMG72LSZD7RJQALAOCO2GPWTS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An Empirical Study of Automated Mislabel Detection in Real World Vision Datasets","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","stat.AP"],"primary_cat":"cs.CV","authors_text":"Andrew Y. Ng, Brian Wesley Hill, Felipe Godoy, Ishan Sabane, Jeremy Irvin, Maya Srikanth","submitted_at":"2023-12-02T19:33:42Z","abstract_excerpt":"Major advancements in computer vision can primarily be attributed to the use of labeled datasets. However, acquiring labels for datasets often results in errors which can harm model performance. Recent works have proposed methods to automatically identify mislabeled images, but developing strategies to effectively implement them in real world datasets has been sparsely explored. Towards improved data-centric methods for cleaning real world vision datasets, we first conduct more than 200 experiments carefully benchmarking recently developed automated mislabel detection methods on multiple datas"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.02200","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/2312.02200/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":"2026-07-05T07:20:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8ssdFa6btVxcqpa7+8JFYePfy8bhVTY5LyhaOWY4yDAYdX6b8LxaJ/EqEJVU+2feGZxmYQDs/+VJVR4O9LplCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T04:14:14.942625Z"},"content_sha256":"bafb45112f220d45cf9a319dc287d55cad3e5211e568b1b16d63788f3f63a808","schema_version":"1.0","event_id":"sha256:bafb45112f220d45cf9a319dc287d55cad3e5211e568b1b16d63788f3f63a808"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XLMG72LSZD7RJQALAOCO2GPWTS/bundle.json","state_url":"https://pith.science/pith/XLMG72LSZD7RJQALAOCO2GPWTS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XLMG72LSZD7RJQALAOCO2GPWTS/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":"2026-08-15T04:14:14Z","links":{"resolver":"https://pith.science/pith/XLMG72LSZD7RJQALAOCO2GPWTS","bundle":"https://pith.science/pith/XLMG72LSZD7RJQALAOCO2GPWTS/bundle.json","state":"https://pith.science/pith/XLMG72LSZD7RJQALAOCO2GPWTS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XLMG72LSZD7RJQALAOCO2GPWTS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:XLMG72LSZD7RJQALAOCO2GPWTS","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":"5a5541549618b21fdf2990c33a20d36d4ecec448638675741f5b5e53c0db0cb8","cross_cats_sorted":["cs.AI","stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-02T19:33:42Z","title_canon_sha256":"ea3db9bfc156f2aa24cbbbfaa5aff673fbc8ead1f00665facfd9482448bd12cc"},"schema_version":"1.0","source":{"id":"2312.02200","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.02200","created_at":"2026-07-05T07:20:14Z"},{"alias_kind":"arxiv_version","alias_value":"2312.02200v1","created_at":"2026-07-05T07:20:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.02200","created_at":"2026-07-05T07:20:14Z"},{"alias_kind":"pith_short_12","alias_value":"XLMG72LSZD7R","created_at":"2026-07-05T07:20:14Z"},{"alias_kind":"pith_short_16","alias_value":"XLMG72LSZD7RJQAL","created_at":"2026-07-05T07:20:14Z"},{"alias_kind":"pith_short_8","alias_value":"XLMG72LS","created_at":"2026-07-05T07:20:14Z"}],"graph_snapshots":[{"event_id":"sha256:bafb45112f220d45cf9a319dc287d55cad3e5211e568b1b16d63788f3f63a808","target":"graph","created_at":"2026-07-05T07:20:14Z","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/2312.02200/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Major advancements in computer vision can primarily be attributed to the use of labeled datasets. However, acquiring labels for datasets often results in errors which can harm model performance. Recent works have proposed methods to automatically identify mislabeled images, but developing strategies to effectively implement them in real world datasets has been sparsely explored. Towards improved data-centric methods for cleaning real world vision datasets, we first conduct more than 200 experiments carefully benchmarking recently developed automated mislabel detection methods on multiple datas","authors_text":"Andrew Y. Ng, Brian Wesley Hill, Felipe Godoy, Ishan Sabane, Jeremy Irvin, Maya Srikanth","cross_cats":["cs.AI","stat.AP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-02T19:33:42Z","title":"An Empirical Study of Automated Mislabel Detection in Real World Vision Datasets"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.02200","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":"sha256:7ac2ed9a465af0e431144fcfa3eb28831316571da058cd7827d6aebaace7a1cd","target":"record","created_at":"2026-07-05T07:20:14Z","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":"5a5541549618b21fdf2990c33a20d36d4ecec448638675741f5b5e53c0db0cb8","cross_cats_sorted":["cs.AI","stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-02T19:33:42Z","title_canon_sha256":"ea3db9bfc156f2aa24cbbbfaa5aff673fbc8ead1f00665facfd9482448bd12cc"},"schema_version":"1.0","source":{"id":"2312.02200","kind":"arxiv","version":1}},"canonical_sha256":"bad86fe972c8ff14c00b0384ed19f69c849303226ccd4091d2bc0b5afc3c308c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bad86fe972c8ff14c00b0384ed19f69c849303226ccd4091d2bc0b5afc3c308c","first_computed_at":"2026-07-05T07:20:14.269901Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:20:14.269901Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"D8M+wGZWJ6hoBRuNV74aHkpmuIqS8PtItb9awoXxzooyERmvRlm+oLbPIXlFXNr0Ex2WHRphfcd/mW9i1I7ZDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:20:14.270405Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.02200","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7ac2ed9a465af0e431144fcfa3eb28831316571da058cd7827d6aebaace7a1cd","sha256:bafb45112f220d45cf9a319dc287d55cad3e5211e568b1b16d63788f3f63a808"],"state_sha256":"fa09e2338767450bcbf08eb16df276f6800e3bc5082cf4d791c626e3094370a1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W8ZbyXu+Fj+g/Dg9fXAB6s3/bJhESjYh46tGtEVHvFoPwkjXm4pMmtpSvLyALcji3nBuG4dQlj9bFQibAuEXDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T04:14:14.946677Z","bundle_sha256":"28f7f6fb2b46913deb5e6c6bee6dc42222f28ee06c1ca23f0b9e8318b528dbba"}}