{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:7DITFT7RG37UUHR5JBGUYFZMUL","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":"ee5d89a852b2fef20a19630bef96c18a7cb6b5989f54d330d7fd39e532c1eb88","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-06-19T22:09:47Z","title_canon_sha256":"3f7035360214362670b5c32e2cacd99508a1f7247001d60e76d870e0c2849ed2"},"schema_version":"1.0","source":{"id":"1906.08255","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.08255","created_at":"2026-05-17T23:42:52Z"},{"alias_kind":"arxiv_version","alias_value":"1906.08255v1","created_at":"2026-05-17T23:42:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.08255","created_at":"2026-05-17T23:42:52Z"},{"alias_kind":"pith_short_12","alias_value":"7DITFT7RG37U","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"7DITFT7RG37UUHR5","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"7DITFT7R","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:6939dc6eec41450dc59c3d9c4fca084a0d7d18049127340adbf3211ab086095a","target":"graph","created_at":"2026-05-17T23:42:52Z","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":"MNIST and Fashion MNIST are extremely popular for testing in the machine learning space. Fashion MNIST improves on MNIST by introducing a harder problem, increasing the diversity of testing sets, and more accurately representing a modern computer vision task. In order to increase the data quality of FashionMNIST, this paper investigates near duplicate images between training and testing sets. Near-duplicates between testing and training sets artificially increase the testing accuracy of machine learning models. This paper identifies near-duplicate images in Fashion MNIST and proposes a dataset","authors_text":"Christopher Geier","cross_cats":["cs.CV","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-06-19T22:09:47Z","title":"Training on test data: Removing near duplicates in Fashion-MNIST"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.08255","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":"sha256:9ff15c1d556d27ef13e84a47585973ecdecc64c823a396521aabb750b7c5081e","target":"record","created_at":"2026-05-17T23:42:52Z","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":"ee5d89a852b2fef20a19630bef96c18a7cb6b5989f54d330d7fd39e532c1eb88","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-06-19T22:09:47Z","title_canon_sha256":"3f7035360214362670b5c32e2cacd99508a1f7247001d60e76d870e0c2849ed2"},"schema_version":"1.0","source":{"id":"1906.08255","kind":"arxiv","version":1}},"canonical_sha256":"f8d132cff136ff4a1e3d484d4c172ca2dd251e27620c620b387982d03727f4e2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f8d132cff136ff4a1e3d484d4c172ca2dd251e27620c620b387982d03727f4e2","first_computed_at":"2026-05-17T23:42:52.937421Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:42:52.937421Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0TtTI7wGD6L1bqAIf8xtcRu3Dpl9MxjUw7ivqxQEJwXDwgfjLGoMgyx64PkI6A9BExUAbj5XkBP6n9DRWV2mDw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:42:52.938107Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.08255","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9ff15c1d556d27ef13e84a47585973ecdecc64c823a396521aabb750b7c5081e","sha256:6939dc6eec41450dc59c3d9c4fca084a0d7d18049127340adbf3211ab086095a"],"state_sha256":"eb5e16af092549793cd72aebc8084134e6daa99152b4b74f3d70a28596774e90"}