{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:JOHW6REOOXS2UZUFWQPBNE45YP","short_pith_number":"pith:JOHW6REO","schema_version":"1.0","canonical_sha256":"4b8f6f448e75e5aa6685b41e16939dc3e5391abe759704ec01de0be4f784a1e3","source":{"kind":"arxiv","id":"2506.19845","version":1},"attestation_state":"computed","paper":{"title":"A Comparative Study of NAFNet Baselines for Image Restoration","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"M. Moein Esfahani, Vladislav Esaulov","submitted_at":"2025-06-24T17:59:23Z","abstract_excerpt":"We study NAFNet (Nonlinear Activation Free Network), a simple and efficient deep learning baseline for image restoration. By using CIFAR10 images corrupted with noise and blur, we conduct an ablation study of NAFNet's core components. Our baseline model implements SimpleGate activation, Simplified Channel Activation (SCA), and LayerNormalization. We compare this baseline to different variants that replace or remove components. Quantitative results (PSNR, SSIM) and examples illustrate how each modification affects restoration performance. Our findings support the NAFNet design: the SimpleGate a"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.19845","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-24T17:59:23Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"1cd2cb2175fab113fdca871f0273d2dd0c0d6d427279459e0734531bf6d34227","abstract_canon_sha256":"6940747202cde0e71cd16561d7898eb41b450d781e4bd8a2af8c9b4718b4341d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:26:39.447345Z","signature_b64":"UUMYxxkAtw/iEVV4mmr39u+QLiUy4P9DE+tJVlc+qSViK6f0PPjzq+RYEhZ6TtUuCJYYQynTOzF6GK6RzrcrCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4b8f6f448e75e5aa6685b41e16939dc3e5391abe759704ec01de0be4f784a1e3","last_reissued_at":"2026-07-05T11:26:39.446839Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:26:39.446839Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Comparative Study of NAFNet Baselines for Image Restoration","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"M. Moein Esfahani, Vladislav Esaulov","submitted_at":"2025-06-24T17:59:23Z","abstract_excerpt":"We study NAFNet (Nonlinear Activation Free Network), a simple and efficient deep learning baseline for image restoration. By using CIFAR10 images corrupted with noise and blur, we conduct an ablation study of NAFNet's core components. Our baseline model implements SimpleGate activation, Simplified Channel Activation (SCA), and LayerNormalization. We compare this baseline to different variants that replace or remove components. Quantitative results (PSNR, SSIM) and examples illustrate how each modification affects restoration performance. Our findings support the NAFNet design: the SimpleGate a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.19845","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/2506.19845/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.19845","created_at":"2026-07-05T11:26:39.446903+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.19845v1","created_at":"2026-07-05T11:26:39.446903+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.19845","created_at":"2026-07-05T11:26:39.446903+00:00"},{"alias_kind":"pith_short_12","alias_value":"JOHW6REOOXS2","created_at":"2026-07-05T11:26:39.446903+00:00"},{"alias_kind":"pith_short_16","alias_value":"JOHW6REOOXS2UZUF","created_at":"2026-07-05T11:26:39.446903+00:00"},{"alias_kind":"pith_short_8","alias_value":"JOHW6REO","created_at":"2026-07-05T11:26:39.446903+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/JOHW6REOOXS2UZUFWQPBNE45YP","json":"https://pith.science/pith/JOHW6REOOXS2UZUFWQPBNE45YP.json","graph_json":"https://pith.science/api/pith-number/JOHW6REOOXS2UZUFWQPBNE45YP/graph.json","events_json":"https://pith.science/api/pith-number/JOHW6REOOXS2UZUFWQPBNE45YP/events.json","paper":"https://pith.science/paper/JOHW6REO"},"agent_actions":{"view_html":"https://pith.science/pith/JOHW6REOOXS2UZUFWQPBNE45YP","download_json":"https://pith.science/pith/JOHW6REOOXS2UZUFWQPBNE45YP.json","view_paper":"https://pith.science/paper/JOHW6REO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.19845&json=true","fetch_graph":"https://pith.science/api/pith-number/JOHW6REOOXS2UZUFWQPBNE45YP/graph.json","fetch_events":"https://pith.science/api/pith-number/JOHW6REOOXS2UZUFWQPBNE45YP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JOHW6REOOXS2UZUFWQPBNE45YP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JOHW6REOOXS2UZUFWQPBNE45YP/action/storage_attestation","attest_author":"https://pith.science/pith/JOHW6REOOXS2UZUFWQPBNE45YP/action/author_attestation","sign_citation":"https://pith.science/pith/JOHW6REOOXS2UZUFWQPBNE45YP/action/citation_signature","submit_replication":"https://pith.science/pith/JOHW6REOOXS2UZUFWQPBNE45YP/action/replication_record"}},"created_at":"2026-07-05T11:26:39.446903+00:00","updated_at":"2026-07-05T11:26:39.446903+00:00"}