{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:KPHL7WYPLSRXYR7BFASDL5ONVJ","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":"a128e7584c2d47dd93fa9b135ea35bada41ab99ebb52b7e254e9e227fd6ad2c2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-13T19:07:14Z","title_canon_sha256":"c5d87fceef56652ad4bfd680edd7521c4b5995b32b4cf197c3c77144ae2cab30"},"schema_version":"1.0","source":{"id":"2605.14045","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.14045","created_at":"2026-05-17T23:39:12Z"},{"alias_kind":"arxiv_version","alias_value":"2605.14045v1","created_at":"2026-05-17T23:39:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.14045","created_at":"2026-05-17T23:39:12Z"},{"alias_kind":"pith_short_12","alias_value":"KPHL7WYPLSRX","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"KPHL7WYPLSRXYR7B","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"KPHL7WYP","created_at":"2026-05-18T12:33:37Z"}],"graph_snapshots":[{"event_id":"sha256:721c6104040bd11c5991331a4079f2f273e2b8c480cd3e5d8409e578147d5b93","target":"graph","created_at":"2026-05-17T23:39:12Z","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":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"PVRF improves both fidelity and perceptual quality over state-of-the-art baselines, with strong cross-dataset generalization on single and combined degradations."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"Zero-shot soft weather perceptions produced by frozen VLMs via the AWR-QA module are sufficiently accurate and informative to condition the restoration networks effectively through AMN and WWA."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"PVRF combines zero-shot VLM-based weather perception with perception-adaptive rectified flow refinement to achieve all-in-one adverse weather removal with improved fidelity and cross-dataset generalization."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"PVRF uses zero-shot weather perceptions from frozen vision-language models to guide a velocity-constrained rectified flow that refines restoration anchors for multiple adverse degradations."}],"snapshot_sha256":"9b776bbb19dd19ca86839ad690679e00b9dec62a88a17ee530cbe98526d7a103"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Adverse weather removal (AWR) in real-world images remains challenging due to heterogeneous and unseen degradations, while distortion-driven training often yields overly smooth results. We propose PVRF, a unified framework that integrates zero-shot soft weather perceptions with velocity-constrained rectified-flow refinement. PVRF introduces an AWR-specific question answering module (AWR-QA) that uses frozen vision--language models (VLMs) to estimate soft probabilities of weather types and low-level attribute scores. These perceptions condition restoration networks via attribute-modulated norma","authors_text":"Guangtao Zhai, Guanhua Zhao, Han Zhou, Jun Chen, Shahab Asoodeh, Terry Ji, Wei Dong, Xiaohong Liu, Yulun Zhang","cross_cats":[],"headline":"PVRF uses zero-shot weather perceptions from frozen vision-language models to guide a velocity-constrained rectified flow that refines restoration anchors for multiple adverse degradations.","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-13T19:07:14Z","title":"PVRF: All-in-one Adverse Weather Removal via Prior-modulated and Velocity-constrained Rectified Flow"},"references":{"count":49,"internal_anchors":1,"resolved_work":49,"sample":[{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":1,"title":"The perception-distortion tradeoff","work_id":"8f7c1692-5452-4dc1-97b6-56c11153d5f8","year":2018},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":2,"title":"Unirestore: Unified perceptual and task-oriented image restoration model using diffusion prior","work_id":"acbdda1c-5bf7-432a-bff7-a505cc3f3e73","year":2025},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":3,"title":"Simple baselines for image restoration","work_id":"0e714e9d-2b6b-4cda-ae2e-3c9d63bb1d5d","year":2022},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":4,"title":"All snow removed: Single image desnowing algorithm using hierarchical dual-tree complex wavelet representation and contradict channel loss","work_id":"ff5d9456-46bf-4231-839e-d2b356bf1c0a","year":2021},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":5,"title":"Bio-inspired image restoration","work_id":"f2b9bd5f-9bf0-42f2-a338-e751fc8c71e5","year":2025}],"snapshot_sha256":"e33c2f6542eb037ff4286df1eeb0f68be18962cfbe54fdb3af14c5733bc49bae"},"source":{"id":"2605.14045","kind":"arxiv","version":1},"verdict":{"created_at":"2026-05-15T05:41:19.488862Z","id":"6cc8dc28-3b0d-4924-86f6-2a7b1e8b2e6b","model_set":{"reader":"grok-4.3"},"one_line_summary":"PVRF combines zero-shot VLM-based weather perception with perception-adaptive rectified flow refinement to achieve all-in-one adverse weather removal with improved fidelity and cross-dataset generalization.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"PVRF uses zero-shot weather perceptions from frozen vision-language models to guide a velocity-constrained rectified flow that refines restoration anchors for multiple adverse degradations.","strongest_claim":"PVRF improves both fidelity and perceptual quality over state-of-the-art baselines, with strong cross-dataset generalization on single and combined degradations.","weakest_assumption":"Zero-shot soft weather perceptions produced by frozen VLMs via the AWR-QA module are sufficiently accurate and informative to condition the restoration networks effectively through AMN and WWA."}},"verdict_id":"6cc8dc28-3b0d-4924-86f6-2a7b1e8b2e6b"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:032df3881066aa8bc927a06b5244ceab4d65769702c35f1842516844a0a37996","target":"record","created_at":"2026-05-17T23:39:12Z","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":"a128e7584c2d47dd93fa9b135ea35bada41ab99ebb52b7e254e9e227fd6ad2c2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-13T19:07:14Z","title_canon_sha256":"c5d87fceef56652ad4bfd680edd7521c4b5995b32b4cf197c3c77144ae2cab30"},"schema_version":"1.0","source":{"id":"2605.14045","kind":"arxiv","version":1}},"canonical_sha256":"53cebfdb0f5ca37c47e1282435f5cdaa786818917b8a2c5b6c981be4e5f20276","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"53cebfdb0f5ca37c47e1282435f5cdaa786818917b8a2c5b6c981be4e5f20276","first_computed_at":"2026-05-17T23:39:12.702537Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:39:12.702537Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OntnjIuRtX82V/+BnNQRDOWos2WCW1Ugqkg91Dk7uqoxYhp05uB8dC4y7uQqfXo4MklSuC6sIQ23ZMfOcfIqAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:39:12.703180Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.14045","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:032df3881066aa8bc927a06b5244ceab4d65769702c35f1842516844a0a37996","sha256:721c6104040bd11c5991331a4079f2f273e2b8c480cd3e5d8409e578147d5b93"],"state_sha256":"5899fa1a62faeb896d5684091a1193346bd666ef7f21b6de33b055ede74a8104"}