{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:PLMZ53QOBKIS7RHIQQ7C352CWF","short_pith_number":"pith:PLMZ53QO","canonical_record":{"source":{"id":"2503.23717","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-31T04:37:18Z","cross_cats_sorted":[],"title_canon_sha256":"6a8823c4a0a90f98b754d4c10a39aa0d2a841d7880ee8dbc0efd0c21bf45862a","abstract_canon_sha256":"af196fe8563c9f71c8d7e67852f2cc0550ae6cc927d90c43e767b85cf7ca9277"},"schema_version":"1.0"},"canonical_sha256":"7ad99eee0e0a912fc4e8843e2df742b16a432c35be722976f11f06e9ecfc2279","source":{"kind":"arxiv","id":"2503.23717","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.23717","created_at":"2026-07-05T10:41:58Z"},{"alias_kind":"arxiv_version","alias_value":"2503.23717v1","created_at":"2026-07-05T10:41:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.23717","created_at":"2026-07-05T10:41:58Z"},{"alias_kind":"pith_short_12","alias_value":"PLMZ53QOBKIS","created_at":"2026-07-05T10:41:58Z"},{"alias_kind":"pith_short_16","alias_value":"PLMZ53QOBKIS7RHI","created_at":"2026-07-05T10:41:58Z"},{"alias_kind":"pith_short_8","alias_value":"PLMZ53QO","created_at":"2026-07-05T10:41:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:PLMZ53QOBKIS7RHIQQ7C352CWF","target":"record","payload":{"canonical_record":{"source":{"id":"2503.23717","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-31T04:37:18Z","cross_cats_sorted":[],"title_canon_sha256":"6a8823c4a0a90f98b754d4c10a39aa0d2a841d7880ee8dbc0efd0c21bf45862a","abstract_canon_sha256":"af196fe8563c9f71c8d7e67852f2cc0550ae6cc927d90c43e767b85cf7ca9277"},"schema_version":"1.0"},"canonical_sha256":"7ad99eee0e0a912fc4e8843e2df742b16a432c35be722976f11f06e9ecfc2279","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:41:58.434494Z","signature_b64":"KqQqHn4yy0iItjtk72m3MBcGmsp4AMnT7SiJedUtCKVqdm3KzI3rSW+F6k2W0X6sLTckawtiCeigj7rfEhFyDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7ad99eee0e0a912fc4e8843e2df742b16a432c35be722976f11f06e9ecfc2279","last_reissued_at":"2026-07-05T10:41:58.434065Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:41:58.434065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.23717","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":"2026-07-05T10:41:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OhOn6uFQ9UVrUjZo3xWUNli0uNg8vUJvjl+dtSb0KLLgXpYnG3/Ub83yEMZ11b5haaymuWWUTv3fA2hMTUUMCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T12:15:15.380376Z"},"content_sha256":"5a87ee6f2badaf23e267900751332ebd55387f0c1979ab7c246b58c830d36a8d","schema_version":"1.0","event_id":"sha256:5a87ee6f2badaf23e267900751332ebd55387f0c1979ab7c246b58c830d36a8d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:PLMZ53QOBKIS7RHIQQ7C352CWF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Effective Cloud Removal for Remote Sensing Images by an Improved Mean-Reverting Denoising Model with Elucidated Design Space","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jihong Guan, Shuigeng Zhou, Wengen Li, Yichao Zhang, Yi Liu","submitted_at":"2025-03-31T04:37:18Z","abstract_excerpt":"Cloud removal (CR) remains a challenging task in remote sensing image processing. Although diffusion models (DM) exhibit strong generative capabilities, their direct applications to CR are suboptimal, as they generate cloudless images from random noise, ignoring inherent information in cloudy inputs. To overcome this drawback, we develop a new CR model EMRDM based on mean-reverting diffusion models (MRDMs) to establish a direct diffusion process between cloudy and cloudless images. Compared to current MRDMs, EMRDM offers a modular framework with updatable modules and an elucidated design space"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.23717","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/2503.23717/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":"2026-07-05T10:41:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R3Y2nu9OH0HIVElHnjQNRWo16Ixm7Qs6w8/o+QCQ3FSqu4OcfwGE8iW2ZJezycettYXDkJzPMbeI9nmTfM/bBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T12:15:15.380746Z"},"content_sha256":"753e4cd07ee74e1cd5bab946ef869243833573f9465f7f443fdfa02d61f4b4bc","schema_version":"1.0","event_id":"sha256:753e4cd07ee74e1cd5bab946ef869243833573f9465f7f443fdfa02d61f4b4bc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PLMZ53QOBKIS7RHIQQ7C352CWF/bundle.json","state_url":"https://pith.science/pith/PLMZ53QOBKIS7RHIQQ7C352CWF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PLMZ53QOBKIS7RHIQQ7C352CWF/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":"2026-08-21T12:15:15Z","links":{"resolver":"https://pith.science/pith/PLMZ53QOBKIS7RHIQQ7C352CWF","bundle":"https://pith.science/pith/PLMZ53QOBKIS7RHIQQ7C352CWF/bundle.json","state":"https://pith.science/pith/PLMZ53QOBKIS7RHIQQ7C352CWF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PLMZ53QOBKIS7RHIQQ7C352CWF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:PLMZ53QOBKIS7RHIQQ7C352CWF","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":"af196fe8563c9f71c8d7e67852f2cc0550ae6cc927d90c43e767b85cf7ca9277","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-31T04:37:18Z","title_canon_sha256":"6a8823c4a0a90f98b754d4c10a39aa0d2a841d7880ee8dbc0efd0c21bf45862a"},"schema_version":"1.0","source":{"id":"2503.23717","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.23717","created_at":"2026-07-05T10:41:58Z"},{"alias_kind":"arxiv_version","alias_value":"2503.23717v1","created_at":"2026-07-05T10:41:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.23717","created_at":"2026-07-05T10:41:58Z"},{"alias_kind":"pith_short_12","alias_value":"PLMZ53QOBKIS","created_at":"2026-07-05T10:41:58Z"},{"alias_kind":"pith_short_16","alias_value":"PLMZ53QOBKIS7RHI","created_at":"2026-07-05T10:41:58Z"},{"alias_kind":"pith_short_8","alias_value":"PLMZ53QO","created_at":"2026-07-05T10:41:58Z"}],"graph_snapshots":[{"event_id":"sha256:753e4cd07ee74e1cd5bab946ef869243833573f9465f7f443fdfa02d61f4b4bc","target":"graph","created_at":"2026-07-05T10:41:58Z","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/2503.23717/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Cloud removal (CR) remains a challenging task in remote sensing image processing. Although diffusion models (DM) exhibit strong generative capabilities, their direct applications to CR are suboptimal, as they generate cloudless images from random noise, ignoring inherent information in cloudy inputs. To overcome this drawback, we develop a new CR model EMRDM based on mean-reverting diffusion models (MRDMs) to establish a direct diffusion process between cloudy and cloudless images. Compared to current MRDMs, EMRDM offers a modular framework with updatable modules and an elucidated design space","authors_text":"Jihong Guan, Shuigeng Zhou, Wengen Li, Yichao Zhang, Yi Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-31T04:37:18Z","title":"Effective Cloud Removal for Remote Sensing Images by an Improved Mean-Reverting Denoising Model with Elucidated Design Space"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.23717","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":"sha256:5a87ee6f2badaf23e267900751332ebd55387f0c1979ab7c246b58c830d36a8d","target":"record","created_at":"2026-07-05T10:41:58Z","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":"af196fe8563c9f71c8d7e67852f2cc0550ae6cc927d90c43e767b85cf7ca9277","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-31T04:37:18Z","title_canon_sha256":"6a8823c4a0a90f98b754d4c10a39aa0d2a841d7880ee8dbc0efd0c21bf45862a"},"schema_version":"1.0","source":{"id":"2503.23717","kind":"arxiv","version":1}},"canonical_sha256":"7ad99eee0e0a912fc4e8843e2df742b16a432c35be722976f11f06e9ecfc2279","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7ad99eee0e0a912fc4e8843e2df742b16a432c35be722976f11f06e9ecfc2279","first_computed_at":"2026-07-05T10:41:58.434065Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:41:58.434065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KqQqHn4yy0iItjtk72m3MBcGmsp4AMnT7SiJedUtCKVqdm3KzI3rSW+F6k2W0X6sLTckawtiCeigj7rfEhFyDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:41:58.434494Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.23717","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5a87ee6f2badaf23e267900751332ebd55387f0c1979ab7c246b58c830d36a8d","sha256:753e4cd07ee74e1cd5bab946ef869243833573f9465f7f443fdfa02d61f4b4bc"],"state_sha256":"f1bf0468bf227687dc9ac66512f6730d1cf95a962a8543923e1f73c398d79538"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5SBWUSZJzNR1/EBbTmcpQ0nlwXB6RqPdC8URcVZndJ3ZLx4MEmspBo7WU0tSQNv0KpIFzr4fHoTSdZLk/sEyBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T12:15:15.383087Z","bundle_sha256":"457c4f829c3ac02828694551a2c252737b1386996548d2712499482fe04b6c5b"}}