{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:V6IXOG6OQJRTMLEJLKCF56YHTW","short_pith_number":"pith:V6IXOG6O","canonical_record":{"source":{"id":"2412.00076","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-26T16:47:59Z","cross_cats_sorted":[],"title_canon_sha256":"05e1c1c150705900905e3945074d0b8eaa46a1276d00c9f31e09e96ab94b76a6","abstract_canon_sha256":"f1514eea9edebcc82cbe36cc85524cda83921ed1a5f03e7dc083aaf57cec782d"},"schema_version":"1.0"},"canonical_sha256":"af91771bce8263362c895a845efb079da6765163e0dff3cc4a43577b84ec254f","source":{"kind":"arxiv","id":"2412.00076","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.00076","created_at":"2026-07-05T09:42:35Z"},{"alias_kind":"arxiv_version","alias_value":"2412.00076v1","created_at":"2026-07-05T09:42:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.00076","created_at":"2026-07-05T09:42:35Z"},{"alias_kind":"pith_short_12","alias_value":"V6IXOG6OQJRT","created_at":"2026-07-05T09:42:35Z"},{"alias_kind":"pith_short_16","alias_value":"V6IXOG6OQJRTMLEJ","created_at":"2026-07-05T09:42:35Z"},{"alias_kind":"pith_short_8","alias_value":"V6IXOG6O","created_at":"2026-07-05T09:42:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:V6IXOG6OQJRTMLEJLKCF56YHTW","target":"record","payload":{"canonical_record":{"source":{"id":"2412.00076","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-26T16:47:59Z","cross_cats_sorted":[],"title_canon_sha256":"05e1c1c150705900905e3945074d0b8eaa46a1276d00c9f31e09e96ab94b76a6","abstract_canon_sha256":"f1514eea9edebcc82cbe36cc85524cda83921ed1a5f03e7dc083aaf57cec782d"},"schema_version":"1.0"},"canonical_sha256":"af91771bce8263362c895a845efb079da6765163e0dff3cc4a43577b84ec254f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:42:35.952719Z","signature_b64":"HQzHPEWbLZ/yMrtl6I5lMO/J5GWqmDtBBEyPrOFllu4NNYgntaQ4TLYBjX1wmvH1oyE5jgN+z9nOJf5yoah8Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"af91771bce8263362c895a845efb079da6765163e0dff3cc4a43577b84ec254f","last_reissued_at":"2026-07-05T09:42:35.952209Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:42:35.952209Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.00076","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":"2026-07-05T09:42:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tyOa3oSmB3l+IH1Q77mbSYnuIWKI+01wsWBL+MKjEc1EDieV4aUhVE1iTMt7zGMI0fPVT/zQXCh3cxCJvxDZAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T23:13:51.222350Z"},"content_sha256":"4b8954ac51f9af662c2203ec475b4fbe4a286e34a1f92bd72fb8b465afc69a21","schema_version":"1.0","event_id":"sha256:4b8954ac51f9af662c2203ec475b4fbe4a286e34a1f92bd72fb8b465afc69a21"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:V6IXOG6OQJRTMLEJLKCF56YHTW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Flaws of ImageNet, Computer Vision's Favourite Dataset","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Illia Volkov, Jiri Matas, Katerina Hanzelkova, Klara Janouskova, Nikita Kisel","submitted_at":"2024-11-26T16:47:59Z","abstract_excerpt":"Since its release, ImageNet-1k dataset has become a gold standard for evaluating model performance. It has served as the foundation for numerous other datasets and training tasks in computer vision. As models have improved in accuracy, issues related to label correctness have become increasingly apparent. In this blog post, we analyze the issues in the ImageNet-1k dataset, including incorrect labels, overlapping or ambiguous class definitions, training-evaluation domain shifts, and image duplicates. The solutions for some problems are straightforward. For others, we hope to start a broader con"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.00076","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/2412.00076/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":"2026-07-05T09:42:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ktAYajxxTmaB/x3nCIrCaqzHgXW9RX+jkepHhibsrZmOGzswXB7iRj9ZCY6RwznPMrcMhUblNVbIUcGrADIACw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T23:13:51.222861Z"},"content_sha256":"c8ebdabea667112ce8f2ffae479bbadf7480c22d70abfd77b4f8f4faab6b8364","schema_version":"1.0","event_id":"sha256:c8ebdabea667112ce8f2ffae479bbadf7480c22d70abfd77b4f8f4faab6b8364"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V6IXOG6OQJRTMLEJLKCF56YHTW/bundle.json","state_url":"https://pith.science/pith/V6IXOG6OQJRTMLEJLKCF56YHTW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V6IXOG6OQJRTMLEJLKCF56YHTW/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":"2026-08-10T23:13:51Z","links":{"resolver":"https://pith.science/pith/V6IXOG6OQJRTMLEJLKCF56YHTW","bundle":"https://pith.science/pith/V6IXOG6OQJRTMLEJLKCF56YHTW/bundle.json","state":"https://pith.science/pith/V6IXOG6OQJRTMLEJLKCF56YHTW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V6IXOG6OQJRTMLEJLKCF56YHTW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:V6IXOG6OQJRTMLEJLKCF56YHTW","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":"f1514eea9edebcc82cbe36cc85524cda83921ed1a5f03e7dc083aaf57cec782d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-26T16:47:59Z","title_canon_sha256":"05e1c1c150705900905e3945074d0b8eaa46a1276d00c9f31e09e96ab94b76a6"},"schema_version":"1.0","source":{"id":"2412.00076","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.00076","created_at":"2026-07-05T09:42:35Z"},{"alias_kind":"arxiv_version","alias_value":"2412.00076v1","created_at":"2026-07-05T09:42:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.00076","created_at":"2026-07-05T09:42:35Z"},{"alias_kind":"pith_short_12","alias_value":"V6IXOG6OQJRT","created_at":"2026-07-05T09:42:35Z"},{"alias_kind":"pith_short_16","alias_value":"V6IXOG6OQJRTMLEJ","created_at":"2026-07-05T09:42:35Z"},{"alias_kind":"pith_short_8","alias_value":"V6IXOG6O","created_at":"2026-07-05T09:42:35Z"}],"graph_snapshots":[{"event_id":"sha256:c8ebdabea667112ce8f2ffae479bbadf7480c22d70abfd77b4f8f4faab6b8364","target":"graph","created_at":"2026-07-05T09:42:35Z","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/2412.00076/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Since its release, ImageNet-1k dataset has become a gold standard for evaluating model performance. It has served as the foundation for numerous other datasets and training tasks in computer vision. As models have improved in accuracy, issues related to label correctness have become increasingly apparent. In this blog post, we analyze the issues in the ImageNet-1k dataset, including incorrect labels, overlapping or ambiguous class definitions, training-evaluation domain shifts, and image duplicates. The solutions for some problems are straightforward. For others, we hope to start a broader con","authors_text":"Illia Volkov, Jiri Matas, Katerina Hanzelkova, Klara Janouskova, Nikita Kisel","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-26T16:47:59Z","title":"Flaws of ImageNet, Computer Vision's Favourite Dataset"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.00076","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":"sha256:4b8954ac51f9af662c2203ec475b4fbe4a286e34a1f92bd72fb8b465afc69a21","target":"record","created_at":"2026-07-05T09:42:35Z","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":"f1514eea9edebcc82cbe36cc85524cda83921ed1a5f03e7dc083aaf57cec782d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-26T16:47:59Z","title_canon_sha256":"05e1c1c150705900905e3945074d0b8eaa46a1276d00c9f31e09e96ab94b76a6"},"schema_version":"1.0","source":{"id":"2412.00076","kind":"arxiv","version":1}},"canonical_sha256":"af91771bce8263362c895a845efb079da6765163e0dff3cc4a43577b84ec254f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"af91771bce8263362c895a845efb079da6765163e0dff3cc4a43577b84ec254f","first_computed_at":"2026-07-05T09:42:35.952209Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:42:35.952209Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HQzHPEWbLZ/yMrtl6I5lMO/J5GWqmDtBBEyPrOFllu4NNYgntaQ4TLYBjX1wmvH1oyE5jgN+z9nOJf5yoah8Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T09:42:35.952719Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.00076","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4b8954ac51f9af662c2203ec475b4fbe4a286e34a1f92bd72fb8b465afc69a21","sha256:c8ebdabea667112ce8f2ffae479bbadf7480c22d70abfd77b4f8f4faab6b8364"],"state_sha256":"e32767d863341791cf54d6b0011582ef99f75f7af6d31878a9dec7e4fb004543"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TicqqLHWKdl5q09eNIjMKNThem/4DkpwCSC/YbNllwPYRX7pJkuLaIhtbflGPjcSiXP8HlQ7b/8w0SuoEDQ/Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T23:13:51.227040Z","bundle_sha256":"9b6e8bf40e6181c5512662f694160779f801c71bfbbb7fad3335f2704af89cea"}}