{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ADJZFUP3MVQDKPZEGKPCXNARTG","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":"162e8e28da7d562d616f1a72dac8b3968dcc3191627d96faec4d6e3eb8d0363e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-31T19:00:01Z","title_canon_sha256":"7c6a6e528f06dc8c2f32f63455064cd2a86e8690f5253224f98c16f716379b8a"},"schema_version":"1.0","source":{"id":"2501.00603","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.00603","created_at":"2026-07-05T11:17:39Z"},{"alias_kind":"arxiv_version","alias_value":"2501.00603v2","created_at":"2026-07-05T11:17:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.00603","created_at":"2026-07-05T11:17:39Z"},{"alias_kind":"pith_short_12","alias_value":"ADJZFUP3MVQD","created_at":"2026-07-05T11:17:39Z"},{"alias_kind":"pith_short_16","alias_value":"ADJZFUP3MVQDKPZE","created_at":"2026-07-05T11:17:39Z"},{"alias_kind":"pith_short_8","alias_value":"ADJZFUP3","created_at":"2026-07-05T11:17:39Z"}],"graph_snapshots":[{"event_id":"sha256:5cbdeafdcee7431bc9d4e768aa565402400df59829e068284b880fc62c4d5dd7","target":"graph","created_at":"2026-07-05T11:17:39Z","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/2501.00603/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion models have shown exceptional performance in visual generation tasks. Recently, these models have shifted from traditional U-Shaped CNN-Attention hybrid structures to fully transformer-based isotropic architectures. While these transformers exhibit strong scalability and performance, their reliance on complicated self-attention operation results in slow inference speeds. Contrary to these works, we rethink one of the simplest yet fastest module in deep learning, 3x3 Convolution, to construct a scaled-up purely convolutional diffusion model. We first discover that an Encoder-Decoder H","authors_text":"Chao Xu, Chengcheng Wang, Hanting Chen, Jing Han, Yuchen Liang, Yuchuan Tian","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-31T19:00:01Z","title":"DiC: Rethinking Conv3x3 Designs in Diffusion Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.00603","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":"sha256:25283deff10062a8c1c0f1052042ffccd47ae53017c1ec529862c673b8c403b4","target":"record","created_at":"2026-07-05T11:17:39Z","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":"162e8e28da7d562d616f1a72dac8b3968dcc3191627d96faec4d6e3eb8d0363e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-31T19:00:01Z","title_canon_sha256":"7c6a6e528f06dc8c2f32f63455064cd2a86e8690f5253224f98c16f716379b8a"},"schema_version":"1.0","source":{"id":"2501.00603","kind":"arxiv","version":2}},"canonical_sha256":"00d392d1fb6560353f24329e2bb4119981913387e8b4a224d7697926c15bc144","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"00d392d1fb6560353f24329e2bb4119981913387e8b4a224d7697926c15bc144","first_computed_at":"2026-07-05T11:17:39.566200Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:17:39.566200Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SI6CPPO9Xv9XdWEdXF8Fbkidbu6tFYaFPQ+oByU0j8C0Ji1HvbaBuAIaLG+/2JfRjNVt66LsFB47j0wegG5UCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:17:39.566682Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.00603","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:25283deff10062a8c1c0f1052042ffccd47ae53017c1ec529862c673b8c403b4","sha256:5cbdeafdcee7431bc9d4e768aa565402400df59829e068284b880fc62c4d5dd7"],"state_sha256":"60d6c2a2bcf4d91867a657515c3bdf2fa6f936a050503b3d7987f2139ac0615e"}