{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:DJDMSYRREDMHTSC4DIPYD5BXWK","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":"63d4552830c9a3d1cf5cfcea56e350f5c6dff3d2561930ff59036e1fa029931d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-01T16:25:17Z","title_canon_sha256":"03999dc1922fe75847c48f2bdc5a04e2f209b7a77a3769f04cd848ff4eec0f65"},"schema_version":"1.0","source":{"id":"2403.00644","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.00644","created_at":"2026-07-05T08:24:03Z"},{"alias_kind":"arxiv_version","alias_value":"2403.00644v4","created_at":"2026-07-05T08:24:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.00644","created_at":"2026-07-05T08:24:03Z"},{"alias_kind":"pith_short_12","alias_value":"DJDMSYRREDMH","created_at":"2026-07-05T08:24:03Z"},{"alias_kind":"pith_short_16","alias_value":"DJDMSYRREDMHTSC4","created_at":"2026-07-05T08:24:03Z"},{"alias_kind":"pith_short_8","alias_value":"DJDMSYRR","created_at":"2026-07-05T08:24:03Z"}],"graph_snapshots":[{"event_id":"sha256:903031fdbc7d7e17cfd57aaf718cef9b1c71319cf7e3a17d3d1aa096d125f40c","target":"graph","created_at":"2026-07-05T08:24:03Z","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/2403.00644/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion models trained on large-scale datasets have achieved remarkable progress in image synthesis. However, due to the randomness in the diffusion process, they often struggle with handling diverse low-level tasks that require details preservation. To overcome this limitation, we present a new Diff-Plugin framework to enable a single pre-trained diffusion model to generate high-fidelity results across a variety of low-level tasks. Specifically, we first propose a lightweight Task-Plugin module with a dual branch design to provide task-specific priors, guiding the diffusion process in prese","authors_text":"Fang Liu, Nanxuan Zhao, Rynson W.H. Lau, Yuhao Liu, Zhanghan Ke","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-01T16:25:17Z","title":"Diff-Plugin: Revitalizing Details for Diffusion-based Low-level Tasks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.00644","kind":"arxiv","version":4},"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":"sha256:95f837f8fc4aa85b85f78aa2d1603299d17c992abcce31be80fe80c18accf730","target":"record","created_at":"2026-07-05T08:24:03Z","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":"63d4552830c9a3d1cf5cfcea56e350f5c6dff3d2561930ff59036e1fa029931d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-01T16:25:17Z","title_canon_sha256":"03999dc1922fe75847c48f2bdc5a04e2f209b7a77a3769f04cd848ff4eec0f65"},"schema_version":"1.0","source":{"id":"2403.00644","kind":"arxiv","version":4}},"canonical_sha256":"1a46c9623120d879c85c1a1f81f437b28137fc1a22f3d75642096d590a2a261c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1a46c9623120d879c85c1a1f81f437b28137fc1a22f3d75642096d590a2a261c","first_computed_at":"2026-07-05T08:24:03.248429Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:24:03.248429Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MybPGgZKLBE9S8rkCeeH+p79W5U/thWZuT4wBIjd0xpZvtxfSxEEQGEv2zCkK4rGjLHf9ICEyQxd80QwjIEpDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:24:03.248958Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.00644","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:95f837f8fc4aa85b85f78aa2d1603299d17c992abcce31be80fe80c18accf730","sha256:903031fdbc7d7e17cfd57aaf718cef9b1c71319cf7e3a17d3d1aa096d125f40c"],"state_sha256":"2b53684369ff5fa8102ca1d71d56659d713ed4a4480fcf28e0c466a9f861b7ed"}