{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:3PFRRH6GLC2OJNM2ZVCOUY6LVH","short_pith_number":"pith:3PFRRH6G","canonical_record":{"source":{"id":"2502.20679","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-28T03:14:30Z","cross_cats_sorted":[],"title_canon_sha256":"d87b7d8e4a99c652ac41106846aa2e4d7614d1c49666a2b2d32d82bea51a978d","abstract_canon_sha256":"a2946f2ce63c870378328f221a5ef6193ae6e0047cce91972695773786f0cd9a"},"schema_version":"1.0"},"canonical_sha256":"dbcb189fc658b4e4b59acd44ea63cba9fbb8ce7a247f0d920fe97633e21b889c","source":{"kind":"arxiv","id":"2502.20679","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.20679","created_at":"2026-07-05T10:21:37Z"},{"alias_kind":"arxiv_version","alias_value":"2502.20679v1","created_at":"2026-07-05T10:21:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.20679","created_at":"2026-07-05T10:21:37Z"},{"alias_kind":"pith_short_12","alias_value":"3PFRRH6GLC2O","created_at":"2026-07-05T10:21:37Z"},{"alias_kind":"pith_short_16","alias_value":"3PFRRH6GLC2OJNM2","created_at":"2026-07-05T10:21:37Z"},{"alias_kind":"pith_short_8","alias_value":"3PFRRH6G","created_at":"2026-07-05T10:21:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:3PFRRH6GLC2OJNM2ZVCOUY6LVH","target":"record","payload":{"canonical_record":{"source":{"id":"2502.20679","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-28T03:14:30Z","cross_cats_sorted":[],"title_canon_sha256":"d87b7d8e4a99c652ac41106846aa2e4d7614d1c49666a2b2d32d82bea51a978d","abstract_canon_sha256":"a2946f2ce63c870378328f221a5ef6193ae6e0047cce91972695773786f0cd9a"},"schema_version":"1.0"},"canonical_sha256":"dbcb189fc658b4e4b59acd44ea63cba9fbb8ce7a247f0d920fe97633e21b889c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:21:37.535091Z","signature_b64":"6ow7FDQq0T0sFZYIUhziopjIJEHHXAq/gKBdelzdYNFI++CaP6ZNJYX98RRxlo5M9uLS5zseci3Qo6wlNUnVCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dbcb189fc658b4e4b59acd44ea63cba9fbb8ce7a247f0d920fe97633e21b889c","last_reissued_at":"2026-07-05T10:21:37.534548Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:21:37.534548Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.20679","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:21:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kAvaKhjcXNoSooBBSUGgdVgg2nPoWmt1gwvOlQQwpNuNX1UdXhmuIic+PCWUI6yauurqUu79mfCTus1aOHmyAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T02:34:33.792627Z"},"content_sha256":"7cc4468b2795e544876aec78ec94ae1748bda3a0c1526eb9d2734d72dfdac1b2","schema_version":"1.0","event_id":"sha256:7cc4468b2795e544876aec78ec94ae1748bda3a0c1526eb9d2734d72dfdac1b2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:3PFRRH6GLC2OJNM2ZVCOUY6LVH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Diffusion Restoration Adapter for Real-World Image Restoration","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hanbang Liang, Weihui Deng, Zhen Wang","submitted_at":"2025-02-28T03:14:30Z","abstract_excerpt":"Diffusion models have demonstrated their powerful image generation capabilities, effectively fitting highly complex image distributions. These models can serve as strong priors for image restoration. Existing methods often utilize techniques like ControlNet to sample high quality images with low quality images from these priors. However, ControlNet typically involves copying a large part of the original network, resulting in a significantly large number of parameters as the prior scales up. In this paper, we propose a relatively lightweight Adapter that leverages the powerful generative capabi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.20679","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/2502.20679/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:21:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j9owFWO6R0ypu0ViI0fyyhaV1+599/bvViJme8pptijVPKKWrUvRjphmJmM8+9XSlYzu74fRxR7oCrpc4jAzBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T02:34:33.793154Z"},"content_sha256":"7020448bac2663203f0e3cf8a599bfd8c791aa722e90bf55865743dea3487b36","schema_version":"1.0","event_id":"sha256:7020448bac2663203f0e3cf8a599bfd8c791aa722e90bf55865743dea3487b36"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3PFRRH6GLC2OJNM2ZVCOUY6LVH/bundle.json","state_url":"https://pith.science/pith/3PFRRH6GLC2OJNM2ZVCOUY6LVH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3PFRRH6GLC2OJNM2ZVCOUY6LVH/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-08T02:34:33Z","links":{"resolver":"https://pith.science/pith/3PFRRH6GLC2OJNM2ZVCOUY6LVH","bundle":"https://pith.science/pith/3PFRRH6GLC2OJNM2ZVCOUY6LVH/bundle.json","state":"https://pith.science/pith/3PFRRH6GLC2OJNM2ZVCOUY6LVH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3PFRRH6GLC2OJNM2ZVCOUY6LVH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3PFRRH6GLC2OJNM2ZVCOUY6LVH","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":"a2946f2ce63c870378328f221a5ef6193ae6e0047cce91972695773786f0cd9a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-28T03:14:30Z","title_canon_sha256":"d87b7d8e4a99c652ac41106846aa2e4d7614d1c49666a2b2d32d82bea51a978d"},"schema_version":"1.0","source":{"id":"2502.20679","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.20679","created_at":"2026-07-05T10:21:37Z"},{"alias_kind":"arxiv_version","alias_value":"2502.20679v1","created_at":"2026-07-05T10:21:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.20679","created_at":"2026-07-05T10:21:37Z"},{"alias_kind":"pith_short_12","alias_value":"3PFRRH6GLC2O","created_at":"2026-07-05T10:21:37Z"},{"alias_kind":"pith_short_16","alias_value":"3PFRRH6GLC2OJNM2","created_at":"2026-07-05T10:21:37Z"},{"alias_kind":"pith_short_8","alias_value":"3PFRRH6G","created_at":"2026-07-05T10:21:37Z"}],"graph_snapshots":[{"event_id":"sha256:7020448bac2663203f0e3cf8a599bfd8c791aa722e90bf55865743dea3487b36","target":"graph","created_at":"2026-07-05T10:21:37Z","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/2502.20679/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion models have demonstrated their powerful image generation capabilities, effectively fitting highly complex image distributions. These models can serve as strong priors for image restoration. Existing methods often utilize techniques like ControlNet to sample high quality images with low quality images from these priors. However, ControlNet typically involves copying a large part of the original network, resulting in a significantly large number of parameters as the prior scales up. In this paper, we propose a relatively lightweight Adapter that leverages the powerful generative capabi","authors_text":"Hanbang Liang, Weihui Deng, Zhen Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-28T03:14:30Z","title":"Diffusion Restoration Adapter for Real-World Image Restoration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.20679","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":"sha256:7cc4468b2795e544876aec78ec94ae1748bda3a0c1526eb9d2734d72dfdac1b2","target":"record","created_at":"2026-07-05T10:21:37Z","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":"a2946f2ce63c870378328f221a5ef6193ae6e0047cce91972695773786f0cd9a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-28T03:14:30Z","title_canon_sha256":"d87b7d8e4a99c652ac41106846aa2e4d7614d1c49666a2b2d32d82bea51a978d"},"schema_version":"1.0","source":{"id":"2502.20679","kind":"arxiv","version":1}},"canonical_sha256":"dbcb189fc658b4e4b59acd44ea63cba9fbb8ce7a247f0d920fe97633e21b889c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dbcb189fc658b4e4b59acd44ea63cba9fbb8ce7a247f0d920fe97633e21b889c","first_computed_at":"2026-07-05T10:21:37.534548Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:21:37.534548Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6ow7FDQq0T0sFZYIUhziopjIJEHHXAq/gKBdelzdYNFI++CaP6ZNJYX98RRxlo5M9uLS5zseci3Qo6wlNUnVCA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:21:37.535091Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.20679","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7cc4468b2795e544876aec78ec94ae1748bda3a0c1526eb9d2734d72dfdac1b2","sha256:7020448bac2663203f0e3cf8a599bfd8c791aa722e90bf55865743dea3487b36"],"state_sha256":"def0362e1095e0d60a3f42cb29ac33955b1ca1c9c558a6883f2fde5d2a698ccc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2J5a8EKzmpI+GBuvoFGqkiaIZYjCJtoGfujj8xusxT1Aqbdlj0pae8YNkSwjd9ENw12wgW/AIPMWjjerXn1eCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T02:34:33.797462Z","bundle_sha256":"b09524934fae09672a528027877bcb2118389c1b19a7fd101b91eede9b7f48de"}}