{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:3E5UYKBLZHBZRURQR6V6F3LR7I","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":"89b35ee4ef3ddcf98b46a415dc872c941fe8bd7493d75c4c963274e8861418b9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-27T15:41:45Z","title_canon_sha256":"fbbbbc1092f0c2d93aa4d00421370c3fbfd616b849f0e3d2b53007f01ca2fc26"},"schema_version":"1.0","source":{"id":"2105.13244","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.13244","created_at":"2026-07-05T02:44:59Z"},{"alias_kind":"arxiv_version","alias_value":"2105.13244v2","created_at":"2026-07-05T02:44:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.13244","created_at":"2026-07-05T02:44:59Z"},{"alias_kind":"pith_short_12","alias_value":"3E5UYKBLZHBZ","created_at":"2026-07-05T02:44:59Z"},{"alias_kind":"pith_short_16","alias_value":"3E5UYKBLZHBZRURQ","created_at":"2026-07-05T02:44:59Z"},{"alias_kind":"pith_short_8","alias_value":"3E5UYKBL","created_at":"2026-07-05T02:44:59Z"}],"graph_snapshots":[{"event_id":"sha256:f207c17385fda3d68c812bbfe4729caa9f8802473aa2312f85ea055d2a020c5b","target":"graph","created_at":"2026-07-05T02:44:59Z","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/2105.13244/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The memorization problem is well-known in the field of computer vision. Liu et al. propose a technique called Early-Learning Regularization, which improves accuracy on the CIFAR datasets when label noise is present. This project replicates their experiments and investigates the performance on a real-world dataset with intrinsic noise. Results show that their experimental results are consistent. We also explore Sharpness-Aware Minimization in addition to SGD and observed a further 14.6 percentage points improvement. Future work includes using all 6 million images and manually clean a fraction o","authors_text":"Alessio Galatolo, Alfred Nilsson, Roderick Karlemstrand, Yineng Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-27T15:41:45Z","title":"Using Early-Learning Regularization to Classify Real-World Noisy Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.13244","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":"sha256:681a30d63323e384e7e4f5ed8e461ec5aa4ac2660c4088b97b04720a887f50b4","target":"record","created_at":"2026-07-05T02:44:59Z","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":"89b35ee4ef3ddcf98b46a415dc872c941fe8bd7493d75c4c963274e8861418b9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-27T15:41:45Z","title_canon_sha256":"fbbbbc1092f0c2d93aa4d00421370c3fbfd616b849f0e3d2b53007f01ca2fc26"},"schema_version":"1.0","source":{"id":"2105.13244","kind":"arxiv","version":2}},"canonical_sha256":"d93b4c282bc9c398d2308fabe2ed71fa135c9b5def4d862449d9fb391fb2bff0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d93b4c282bc9c398d2308fabe2ed71fa135c9b5def4d862449d9fb391fb2bff0","first_computed_at":"2026-07-05T02:44:59.464026Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:44:59.464026Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Pj2SvopRvhJi1GWUfHd5JmR9I1Hun3anAiMEkPhl7TmZt2XU8knMMmsltmdbSvnQTFtG/S8K4UxVJU3HRDTRCg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:44:59.464548Z","signed_message":"canonical_sha256_bytes"},"source_id":"2105.13244","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:681a30d63323e384e7e4f5ed8e461ec5aa4ac2660c4088b97b04720a887f50b4","sha256:f207c17385fda3d68c812bbfe4729caa9f8802473aa2312f85ea055d2a020c5b"],"state_sha256":"1222928f55e578c87ee50215342c3482a2029e34aadd8ec0c740e4330a123a43"}