{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:XN3ONZMHP4TTJYASYP4BW343AP","short_pith_number":"pith:XN3ONZMH","canonical_record":{"source":{"id":"2407.13372","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-18T10:26:53Z","cross_cats_sorted":[],"title_canon_sha256":"61a73ba4c6f8c4e47ac9d5900e9419cd10ef357a2c534365a4c494eb6cf31f37","abstract_canon_sha256":"a7f6e93b0008bc829ee70a663f5427007fe468de32196dcff9c8a5cc36c32700"},"schema_version":"1.0"},"canonical_sha256":"bb76e6e5877f2734e012c3f81b6f9b03d9a7a014224053fc99b2c122429e1e9d","source":{"kind":"arxiv","id":"2407.13372","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.13372","created_at":"2026-07-05T09:50:49Z"},{"alias_kind":"arxiv_version","alias_value":"2407.13372v2","created_at":"2026-07-05T09:50:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.13372","created_at":"2026-07-05T09:50:49Z"},{"alias_kind":"pith_short_12","alias_value":"XN3ONZMHP4TT","created_at":"2026-07-05T09:50:49Z"},{"alias_kind":"pith_short_16","alias_value":"XN3ONZMHP4TTJYAS","created_at":"2026-07-05T09:50:49Z"},{"alias_kind":"pith_short_8","alias_value":"XN3ONZMH","created_at":"2026-07-05T09:50:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:XN3ONZMHP4TTJYASYP4BW343AP","target":"record","payload":{"canonical_record":{"source":{"id":"2407.13372","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-18T10:26:53Z","cross_cats_sorted":[],"title_canon_sha256":"61a73ba4c6f8c4e47ac9d5900e9419cd10ef357a2c534365a4c494eb6cf31f37","abstract_canon_sha256":"a7f6e93b0008bc829ee70a663f5427007fe468de32196dcff9c8a5cc36c32700"},"schema_version":"1.0"},"canonical_sha256":"bb76e6e5877f2734e012c3f81b6f9b03d9a7a014224053fc99b2c122429e1e9d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:50:49.987107Z","signature_b64":"42YJbrE0OD5yR7GBiRBz+8EKCjLtvlxIa7g9FZr9m2sqtJYFwETe9rdG+zaWd0zGkygcN6xbzBEMq/ZKDAD0Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bb76e6e5877f2734e012c3f81b6f9b03d9a7a014224053fc99b2c122429e1e9d","last_reissued_at":"2026-07-05T09:50:49.986602Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:50:49.986602Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.13372","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:50:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vC4eneWlGhvGLv90sF/NfYYN8Qr/e/RInei7/3ViL7NAbn4WimFY5LV02HlKQeNYHezocJm1SoIftemwXesJCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-17T06:19:32.954466Z"},"content_sha256":"f535e119b24a4d046527a4f6358b50f42e882e3177c098fe67cb47bcddbd05e0","schema_version":"1.0","event_id":"sha256:f535e119b24a4d046527a4f6358b50f42e882e3177c098fe67cb47bcddbd05e0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:XN3ONZMHP4TTJYASYP4BW343AP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Restore Anything Model via Efficient Degradation Adaptation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bin Ren, Danda Pani Paudel, Eduard Zamfir, Ming-Hsuan Yang, Nicu Sebe, Radu Timofte, Yawei Li, Yidi Li, Zongwei Wu","submitted_at":"2024-07-18T10:26:53Z","abstract_excerpt":"With the proliferation of mobile devices, the need for an efficient model to restore any degraded image has become increasingly significant and impactful. Traditional approaches typically involve training dedicated models for each specific degradation, resulting in inefficiency and redundancy. More recent solutions either introduce additional modules to learn visual prompts significantly increasing model size or incorporate cross-modal transfer from large language models trained on vast datasets, adding complexity to the system architecture. In contrast, our approach, termed RAM, takes a unifi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.13372","kind":"arxiv","version":2},"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/2407.13372/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":"2026-07-05T09:50:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rv/OPu4HHFYhIt2VUH6yB1vdjR+M+PzExkLcIBRiOnVsib+k2veqhPXCh3FlbINB8ycqyISn156S/Mluue4sBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-17T06:19:32.954838Z"},"content_sha256":"50d25c1820736ec769925e43e7e7e9c3baf3e4a2ae008c17ddc78d365319b0d0","schema_version":"1.0","event_id":"sha256:50d25c1820736ec769925e43e7e7e9c3baf3e4a2ae008c17ddc78d365319b0d0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XN3ONZMHP4TTJYASYP4BW343AP/bundle.json","state_url":"https://pith.science/pith/XN3ONZMHP4TTJYASYP4BW343AP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XN3ONZMHP4TTJYASYP4BW343AP/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":"2026-07-17T06:19:32Z","links":{"resolver":"https://pith.science/pith/XN3ONZMHP4TTJYASYP4BW343AP","bundle":"https://pith.science/pith/XN3ONZMHP4TTJYASYP4BW343AP/bundle.json","state":"https://pith.science/pith/XN3ONZMHP4TTJYASYP4BW343AP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XN3ONZMHP4TTJYASYP4BW343AP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:XN3ONZMHP4TTJYASYP4BW343AP","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":"a7f6e93b0008bc829ee70a663f5427007fe468de32196dcff9c8a5cc36c32700","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-18T10:26:53Z","title_canon_sha256":"61a73ba4c6f8c4e47ac9d5900e9419cd10ef357a2c534365a4c494eb6cf31f37"},"schema_version":"1.0","source":{"id":"2407.13372","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.13372","created_at":"2026-07-05T09:50:49Z"},{"alias_kind":"arxiv_version","alias_value":"2407.13372v2","created_at":"2026-07-05T09:50:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.13372","created_at":"2026-07-05T09:50:49Z"},{"alias_kind":"pith_short_12","alias_value":"XN3ONZMHP4TT","created_at":"2026-07-05T09:50:49Z"},{"alias_kind":"pith_short_16","alias_value":"XN3ONZMHP4TTJYAS","created_at":"2026-07-05T09:50:49Z"},{"alias_kind":"pith_short_8","alias_value":"XN3ONZMH","created_at":"2026-07-05T09:50:49Z"}],"graph_snapshots":[{"event_id":"sha256:50d25c1820736ec769925e43e7e7e9c3baf3e4a2ae008c17ddc78d365319b0d0","target":"graph","created_at":"2026-07-05T09:50:49Z","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/2407.13372/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the proliferation of mobile devices, the need for an efficient model to restore any degraded image has become increasingly significant and impactful. Traditional approaches typically involve training dedicated models for each specific degradation, resulting in inefficiency and redundancy. More recent solutions either introduce additional modules to learn visual prompts significantly increasing model size or incorporate cross-modal transfer from large language models trained on vast datasets, adding complexity to the system architecture. In contrast, our approach, termed RAM, takes a unifi","authors_text":"Bin Ren, Danda Pani Paudel, Eduard Zamfir, Ming-Hsuan Yang, Nicu Sebe, Radu Timofte, Yawei Li, Yidi Li, Zongwei Wu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-18T10:26:53Z","title":"Restore Anything Model via Efficient Degradation Adaptation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.13372","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:f535e119b24a4d046527a4f6358b50f42e882e3177c098fe67cb47bcddbd05e0","target":"record","created_at":"2026-07-05T09:50:49Z","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":"a7f6e93b0008bc829ee70a663f5427007fe468de32196dcff9c8a5cc36c32700","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-18T10:26:53Z","title_canon_sha256":"61a73ba4c6f8c4e47ac9d5900e9419cd10ef357a2c534365a4c494eb6cf31f37"},"schema_version":"1.0","source":{"id":"2407.13372","kind":"arxiv","version":2}},"canonical_sha256":"bb76e6e5877f2734e012c3f81b6f9b03d9a7a014224053fc99b2c122429e1e9d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bb76e6e5877f2734e012c3f81b6f9b03d9a7a014224053fc99b2c122429e1e9d","first_computed_at":"2026-07-05T09:50:49.986602Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:50:49.986602Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"42YJbrE0OD5yR7GBiRBz+8EKCjLtvlxIa7g9FZr9m2sqtJYFwETe9rdG+zaWd0zGkygcN6xbzBEMq/ZKDAD0Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:50:49.987107Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.13372","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f535e119b24a4d046527a4f6358b50f42e882e3177c098fe67cb47bcddbd05e0","sha256:50d25c1820736ec769925e43e7e7e9c3baf3e4a2ae008c17ddc78d365319b0d0"],"state_sha256":"60404bd28bbd658688db40b383b733f656ac163645a73d88adbc7b48a3440095"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I+mmmRtZ8vu9VWeVyqgwjYxwdLJmn9CkWim4ev/7JsjgsV1FGciyqzDVyGPHEaZAKvW4BahCfAmnBDuF7/vaDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-17T06:19:32.957153Z","bundle_sha256":"90279da75c1f81f725f374a55fbe940552bc7b80c4c9f3fa031e393ee3124434"}}