{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NB4ESE4V6NWW3CP6QX5KJA5UQ3","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":"83edb8ffc6a4eb079734e9adc99ac99c6a9d5dd631a978e47c3089f421bc0e43","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-20T17:57:09Z","title_canon_sha256":"ca0aace8be4e98d655e941171c09a5a39942a66ba78ff6a7b3c9b531557eccb8"},"schema_version":"1.0","source":{"id":"2412.16112","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.16112","created_at":"2026-07-05T09:52:35Z"},{"alias_kind":"arxiv_version","alias_value":"2412.16112v1","created_at":"2026-07-05T09:52:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.16112","created_at":"2026-07-05T09:52:35Z"},{"alias_kind":"pith_short_12","alias_value":"NB4ESE4V6NWW","created_at":"2026-07-05T09:52:35Z"},{"alias_kind":"pith_short_16","alias_value":"NB4ESE4V6NWW3CP6","created_at":"2026-07-05T09:52:35Z"},{"alias_kind":"pith_short_8","alias_value":"NB4ESE4V","created_at":"2026-07-05T09:52:35Z"}],"graph_snapshots":[{"event_id":"sha256:a736ba8c25c143dd0a359d2fba506101d6122056c3c77e02699ec86cb954a115","target":"graph","created_at":"2026-07-05T09:52:35Z","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/2412.16112/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion Transformers (DiT) have become a leading architecture in image generation. However, the quadratic complexity of attention mechanisms, which are responsible for modeling token-wise relationships, results in significant latency when generating high-resolution images. To address this issue, we aim at a linear attention mechanism in this paper that reduces the complexity of pre-trained DiTs to linear. We begin our exploration with a comprehensive summary of existing efficient attention mechanisms and identify four key factors crucial for successful linearization of pre-trained DiTs: loca","authors_text":"Songhua Liu, Xinchao Wang, Zhenxiong Tan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-20T17:57:09Z","title":"CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.16112","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:d898b2226d04776c6c07f1d706faf6c7c3d11fa3656f48a7ae926609ef3733a7","target":"record","created_at":"2026-07-05T09:52:35Z","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":"83edb8ffc6a4eb079734e9adc99ac99c6a9d5dd631a978e47c3089f421bc0e43","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-20T17:57:09Z","title_canon_sha256":"ca0aace8be4e98d655e941171c09a5a39942a66ba78ff6a7b3c9b531557eccb8"},"schema_version":"1.0","source":{"id":"2412.16112","kind":"arxiv","version":1}},"canonical_sha256":"6878491395f36d6d89fe85faa483b486e8687f25ba821235e63420f0c58e6c9a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6878491395f36d6d89fe85faa483b486e8687f25ba821235e63420f0c58e6c9a","first_computed_at":"2026-07-05T09:52:35.214157Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:52:35.214157Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Jt4WqFJ3fK0WxIeshGDw8iSXoR6McApMGOoA+23Yy9iCMBXn9uBh7oLA4doHok4FsYv+hdvioafRjxMVXC9sAA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:52:35.214590Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.16112","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d898b2226d04776c6c07f1d706faf6c7c3d11fa3656f48a7ae926609ef3733a7","sha256:a736ba8c25c143dd0a359d2fba506101d6122056c3c77e02699ec86cb954a115"],"state_sha256":"e7410557503e33282ca3f5fbf0426f0c4de1b16a105428332c7550db25f87cd2"}