{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:27MDAFW3ISHX5BVLKDLBPETZPM","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":"b26c5a45709c50c8c4c22713789ef74e77ff743d2331b9256bbc1f6badf9368e","cross_cats_sorted":["cs.CV","eess.IV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-06-04T00:16:02Z","title_canon_sha256":"e2116b4f1bf613a5ae30a888b4e7f1403206544660485270dc9404688acc4e0f"},"schema_version":"1.0","source":{"id":"2006.02595","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2006.02595","created_at":"2026-07-05T01:07:58Z"},{"alias_kind":"arxiv_version","alias_value":"2006.02595v1","created_at":"2026-07-05T01:07:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.02595","created_at":"2026-07-05T01:07:58Z"},{"alias_kind":"pith_short_12","alias_value":"27MDAFW3ISHX","created_at":"2026-07-05T01:07:58Z"},{"alias_kind":"pith_short_16","alias_value":"27MDAFW3ISHX5BVL","created_at":"2026-07-05T01:07:58Z"},{"alias_kind":"pith_short_8","alias_value":"27MDAFW3","created_at":"2026-07-05T01:07:58Z"}],"graph_snapshots":[{"event_id":"sha256:86983f6c757b2147d05688ee20c11d16f0b7f56954aaeba109e21f0fdb30be0f","target":"graph","created_at":"2026-07-05T01:07:58Z","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/2006.02595/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Data augmentations have been widely studied to improve the accuracy and robustness of classifiers. However, the potential of image augmentation in improving GAN models for image synthesis has not been thoroughly investigated in previous studies. In this work, we systematically study the effectiveness of various existing augmentation techniques for GAN training in a variety of settings. We provide insights and guidelines on how to augment images for both vanilla GANs and GANs with regularizations, improving the fidelity of the generated images substantially. Surprisingly, we find that vanilla G","authors_text":"Han Zhang, Sameer Singh, Ting Chen, Zhengli Zhao, Zizhao Zhang","cross_cats":["cs.CV","eess.IV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-06-04T00:16:02Z","title":"Image Augmentations for GAN Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.02595","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":"sha256:12367e4d62250b11e0e2545c5ad168b4f4d1d310b4dce690a26ec9d748b05862","target":"record","created_at":"2026-07-05T01:07:58Z","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":"b26c5a45709c50c8c4c22713789ef74e77ff743d2331b9256bbc1f6badf9368e","cross_cats_sorted":["cs.CV","eess.IV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-06-04T00:16:02Z","title_canon_sha256":"e2116b4f1bf613a5ae30a888b4e7f1403206544660485270dc9404688acc4e0f"},"schema_version":"1.0","source":{"id":"2006.02595","kind":"arxiv","version":1}},"canonical_sha256":"d7d83016db448f7e86ab50d61792797b266c62e754e4b1ed89e8768b543fd9c1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d7d83016db448f7e86ab50d61792797b266c62e754e4b1ed89e8768b543fd9c1","first_computed_at":"2026-07-05T01:07:58.195837Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:07:58.195837Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NndbrWwkDKMJnHCpsk4bAO8xzJjjGxoZdbovKWQctHGjSpACcqp5SDdDrfzUcLMWefEBIzBG4n9Fkl/p4EnEDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:07:58.196393Z","signed_message":"canonical_sha256_bytes"},"source_id":"2006.02595","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:12367e4d62250b11e0e2545c5ad168b4f4d1d310b4dce690a26ec9d748b05862","sha256:86983f6c757b2147d05688ee20c11d16f0b7f56954aaeba109e21f0fdb30be0f"],"state_sha256":"0a4f864b9e1c1a50149a175c2e7a118370ac29e0c79046a0703e3b75e9b4d388"}