{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:OF2VXJVYOL7HJ3YHFKQS37OOJ7","short_pith_number":"pith:OF2VXJVY","canonical_record":{"source":{"id":"2607.16320","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-15T08:57:38Z","cross_cats_sorted":[],"title_canon_sha256":"344f15e8d8bb8e3729d98a61ced7eff52a9cd06a4a4268f6e93acdb9ef5fe29f","abstract_canon_sha256":"13f0985821d49c1697b7b07855ce1b9e962b69a30d40570c225917c108a67801"},"schema_version":"1.0"},"canonical_sha256":"71755ba6b872fe74ef072aa12dfdce4ffc65284facef07ae7f5392235a97ce32","source":{"kind":"arxiv","id":"2607.16320","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.16320","created_at":"2026-07-21T00:20:12Z"},{"alias_kind":"arxiv_version","alias_value":"2607.16320v1","created_at":"2026-07-21T00:20:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.16320","created_at":"2026-07-21T00:20:12Z"},{"alias_kind":"pith_short_12","alias_value":"OF2VXJVYOL7H","created_at":"2026-07-21T00:20:12Z"},{"alias_kind":"pith_short_16","alias_value":"OF2VXJVYOL7HJ3YH","created_at":"2026-07-21T00:20:12Z"},{"alias_kind":"pith_short_8","alias_value":"OF2VXJVY","created_at":"2026-07-21T00:20:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:OF2VXJVYOL7HJ3YHFKQS37OOJ7","target":"record","payload":{"canonical_record":{"source":{"id":"2607.16320","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-15T08:57:38Z","cross_cats_sorted":[],"title_canon_sha256":"344f15e8d8bb8e3729d98a61ced7eff52a9cd06a4a4268f6e93acdb9ef5fe29f","abstract_canon_sha256":"13f0985821d49c1697b7b07855ce1b9e962b69a30d40570c225917c108a67801"},"schema_version":"1.0"},"canonical_sha256":"71755ba6b872fe74ef072aa12dfdce4ffc65284facef07ae7f5392235a97ce32","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-21T00:20:12.119395Z","signature_b64":"tJhOwRhdfLCbA/+CjoDFKvs7tX55U7IIN8AQCirHKfw1mFRW3ULzVz6N328pnd65a2qHqXsuSTXfTwcxPVxcDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"71755ba6b872fe74ef072aa12dfdce4ffc65284facef07ae7f5392235a97ce32","last_reissued_at":"2026-07-21T00:20:12.118411Z","signature_status":"signed_v1","first_computed_at":"2026-07-21T00:20:12.118411Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.16320","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":"2026-07-21T00:20:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"irae30PDbT/fSgwonQgOlx4YdpQBOv4fi38qq/Py9NVw60HWmu9evxzRupDtYqX2fd5AO5salYI13NLTa1j/Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:51:10.413237Z"},"content_sha256":"81341956da81fd3b9aeda8a3b58a3726d9082ca3bae031b31b6c11ca5cc50821","schema_version":"1.0","event_id":"sha256:81341956da81fd3b9aeda8a3b58a3726d9082ca3bae031b31b6c11ca5cc50821"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:OF2VXJVYOL7HJ3YHFKQS37OOJ7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"The Devil is in the Dark Pixels: Toward Brightness Bias-Robust Denoising","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Sungjun Cho, Xiaomeng Li, ZhuangZhuang Chen","submitted_at":"2026-07-15T08:57:38Z","abstract_excerpt":"In this paper, we reveal an important yet overlooked problem in image denoising: under signal-dependent camera noise models, dark regions suffer from inherently low Signal-to-Noise Ratio (SNR), as signal intensity decays far faster than noise variance diminishes, making detail recovery in dark areas fundamentally challenging. Yet rather than compensating for this difficulty, MSE-trained denoisers exacerbate it -- reconstructing dark pixels up to 6x worse relative to their per-band noise floor. This bias stems from two compounding factors: signal-dependent noise inflates bright-pixel residuals,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.16320","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/2607.16320/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":"2026-07-21T00:20:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O0vQzk9NPyWdGgZ+jkfnk0QAkJi3mwd6/xzdJFhvBqB/5p1ZM3UOWStPxdxfa+5wCshrU+obeSBntOIarBeKDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:51:10.414257Z"},"content_sha256":"78da6751e35ca8aa8cdbb0683c6b8fd0b9ac84d4a2e9ffd220bec4f0541c2237","schema_version":"1.0","event_id":"sha256:78da6751e35ca8aa8cdbb0683c6b8fd0b9ac84d4a2e9ffd220bec4f0541c2237"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:OF2VXJVYOL7HJ3YHFKQS37OOJ7","target":"integrity","payload":{"note":"Identifier '10.1109/tip.2017' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","snippet":"Zhang, K., Zuo, W., Chen, Y., Meng, D., Zhang, L.: Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising. IEEE Transactions on Im- age Processing26(7), 3142–3155 (2017).https://doi.org/10.1109/TIP.2017. 26622061, 4 B","arxiv_id":"2607.16320","detector":"doi_compliance","evidence":{"doi":"10.1109/tip.2017","arxiv_id":null,"ref_index":35,"raw_excerpt":"Zhang, K., Zuo, W., Chen, Y., Meng, D., Zhang, L.: Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising. IEEE Transactions on Im- age Processing26(7), 3142–3155 (2017).https://doi.org/10.1109/TIP.2017. 26622061, 4 Brightness Bias in Learned Image Denoising 17","parse_status":"well_formed","verdict_class":"cross_source","checked_sources":["crossref_by_doi","openalex_by_doi","doi_org_head"],"resolution_status":"hard_miss"},"severity":"critical","ref_index":35,"audited_at":"2026-08-02T04:51:00.698715Z","event_type":"pith.integrity.v1","detected_doi":"10.1109/tip.2017","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"unresolvable_identifier","evidence_hash":"7e4448670601e3975371d161dfd3d81e25ca5034fcbc855f24612cdaa9632926","paper_version":1,"verdict_class":"cross_source","resolved_title":null,"detector_version":"1.1.0","detected_arxiv_id":null,"integrity_event_id":17215,"payload_sha256":"7d63cee4fcef692e669c9be033f0458430a788d1034b3582ffc75f46cc28e6ee","signature_b64":"9qqGapkkvNeIN5knqcTi1KHqIcckDVOLlav2HBOVy0tBCQW+50XyjSmWh4gvGOp74LeEI3tiCfXQHDaWFqnrBA==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-02T04:53:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VTosrUtkLWEmlX1y4yECkc8DBbu8N8kZQSDwsFDaIZdV19wdg9fqI7cBygURaTXf8ed7sizH2bKoVDzCjv+XCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:51:10.438462Z"},"content_sha256":"0ceeb1b283c0326b9e04998d6e434c328189e8cbd51d3bf62f9e9b34e6c9a71f","schema_version":"1.0","event_id":"sha256:0ceeb1b283c0326b9e04998d6e434c328189e8cbd51d3bf62f9e9b34e6c9a71f"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:OF2VXJVYOL7HJ3YHFKQS37OOJ7","target":"integrity","payload":{"note":"Identifier '10.1007/s00034-025-03477-z1' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","snippet":"Pathak, K., Bhandari, A.K.: Advances in deep learning and filtering models for medical image denoising: A review of current and future trends. Circuits, Systems, and Signal Processing (2026).https://doi.org/10.1007/s00034-025-03477-z1","arxiv_id":"2607.16320","detector":"doi_compliance","evidence":{"doi":"10.1007/s00034-025-03477-z1","arxiv_id":null,"ref_index":23,"raw_excerpt":"Pathak, K., Bhandari, A.K.: Advances in deep learning and filtering models for medical image denoising: A review of current and future trends. Circuits, Systems, and Signal Processing (2026).https://doi.org/10.1007/s00034-025-03477-z1","parse_status":"well_formed","verdict_class":"cross_source","checked_sources":["crossref_by_doi","openalex_by_doi","doi_org_head"],"resolution_status":"hard_miss"},"severity":"critical","ref_index":23,"audited_at":"2026-08-02T04:51:00.698715Z","event_type":"pith.integrity.v1","detected_doi":"10.1007/s00034-025-03477-z1","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"unresolvable_identifier","evidence_hash":"65a9482fbb520d126aa05f32944b8cefaef581f16f53ad4f484ae96e56b6bb58","paper_version":1,"verdict_class":"cross_source","resolved_title":null,"detector_version":"1.1.0","detected_arxiv_id":null,"integrity_event_id":17214,"payload_sha256":"19f0885ee8fb1434cc32d62d6061689db409656731f206acff6d582ab289b901","signature_b64":"Sh0lytSCRcaja/o/3yfs1gopmMrZRdG/xZMRwLi1lVicFlZyXvDVXpreNTkLTE0HAO8YxNUa8jtp5/uLbTw4CQ==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-02T04:53:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6XiGGh+OgKkcDBHzlwKpKzNOU+K2Z/ejLvuE+rJO5K+vPaGKQJE1V4FY/X1vyUZZGatUMEhO9n5X32nVZqjQBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:51:10.439247Z"},"content_sha256":"0d84822c51c8dbf0024fde545d07d920c29f682d9e63d59556ac14feea7c9a97","schema_version":"1.0","event_id":"sha256:0d84822c51c8dbf0024fde545d07d920c29f682d9e63d59556ac14feea7c9a97"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:OF2VXJVYOL7HJ3YHFKQS37OOJ7","target":"integrity","payload":{"note":"Identifier '10.1137/23m15458591' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","snippet":"Elad, M., Kawar, B., Vaksman, G.: Image denoising: The deep learning revolution and beyond—A survey paper. SIAM Journal on Imaging Sciences16(3), 1594–1654 (2023).https://doi.org/10.1137/23M15458591","arxiv_id":"2607.16320","detector":"doi_compliance","evidence":{"doi":"10.1137/23m15458591","arxiv_id":null,"ref_index":7,"raw_excerpt":"Elad, M., Kawar, B., Vaksman, G.: Image denoising: The deep learning revolution and beyond—A survey paper. SIAM Journal on Imaging Sciences16(3), 1594–1654 (2023).https://doi.org/10.1137/23M15458591","parse_status":"well_formed","verdict_class":"cross_source","checked_sources":["crossref_by_doi","openalex_by_doi","doi_org_head"],"resolution_status":"hard_miss"},"severity":"critical","ref_index":7,"audited_at":"2026-08-02T04:51:00.698715Z","event_type":"pith.integrity.v1","detected_doi":"10.1137/23m15458591","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"unresolvable_identifier","evidence_hash":"4ff79fa7c2dfcccc914bfc480907b73305f908224c5a8d41b52900359571d38f","paper_version":1,"verdict_class":"cross_source","resolved_title":null,"detector_version":"1.1.0","detected_arxiv_id":null,"integrity_event_id":17213,"payload_sha256":"00762d70cf55de9447cb019bfa79b925a028a1f36ef43caf6ff663c405a82acf","signature_b64":"FX1E2Wjc3E0C26H0z2QNIOXZxfxq9KyAvY9y6hs/EI9//5WozNtK+7yAgtRfkAfzCLS55+KIIVCvZxzim3ozCA==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-02T04:53:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WC5t+wcrckJFGhkaeEfgO2h5H4fPpajUeuMEvnFQHPMDjrYTvk8a22qiHmTQ0hiHMh2P8nIm3kz8nx7cgXpkCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:51:10.439998Z"},"content_sha256":"7db8832d487b16bb3710fc8d78e729b34e0587ae683f35cad9cdcc99b024a24f","schema_version":"1.0","event_id":"sha256:7db8832d487b16bb3710fc8d78e729b34e0587ae683f35cad9cdcc99b024a24f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OF2VXJVYOL7HJ3YHFKQS37OOJ7/bundle.json","state_url":"https://pith.science/pith/OF2VXJVYOL7HJ3YHFKQS37OOJ7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OF2VXJVYOL7HJ3YHFKQS37OOJ7/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":"2026-08-05T19:51:10Z","links":{"resolver":"https://pith.science/pith/OF2VXJVYOL7HJ3YHFKQS37OOJ7","bundle":"https://pith.science/pith/OF2VXJVYOL7HJ3YHFKQS37OOJ7/bundle.json","state":"https://pith.science/pith/OF2VXJVYOL7HJ3YHFKQS37OOJ7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OF2VXJVYOL7HJ3YHFKQS37OOJ7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:OF2VXJVYOL7HJ3YHFKQS37OOJ7","merge_version":"pith-open-graph-merge-v1","event_count":5,"valid_event_count":5,"invalid_event_count":0,"equivocation_count":1,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"13f0985821d49c1697b7b07855ce1b9e962b69a30d40570c225917c108a67801","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-15T08:57:38Z","title_canon_sha256":"344f15e8d8bb8e3729d98a61ced7eff52a9cd06a4a4268f6e93acdb9ef5fe29f"},"schema_version":"1.0","source":{"id":"2607.16320","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.16320","created_at":"2026-07-21T00:20:12Z"},{"alias_kind":"arxiv_version","alias_value":"2607.16320v1","created_at":"2026-07-21T00:20:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.16320","created_at":"2026-07-21T00:20:12Z"},{"alias_kind":"pith_short_12","alias_value":"OF2VXJVYOL7H","created_at":"2026-07-21T00:20:12Z"},{"alias_kind":"pith_short_16","alias_value":"OF2VXJVYOL7HJ3YH","created_at":"2026-07-21T00:20:12Z"},{"alias_kind":"pith_short_8","alias_value":"OF2VXJVY","created_at":"2026-07-21T00:20:12Z"}],"graph_snapshots":[{"event_id":"sha256:78da6751e35ca8aa8cdbb0683c6b8fd0b9ac84d4a2e9ffd220bec4f0541c2237","target":"graph","created_at":"2026-07-21T00:20:12Z","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":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2607.16320/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we reveal an important yet overlooked problem in image denoising: under signal-dependent camera noise models, dark regions suffer from inherently low Signal-to-Noise Ratio (SNR), as signal intensity decays far faster than noise variance diminishes, making detail recovery in dark areas fundamentally challenging. Yet rather than compensating for this difficulty, MSE-trained denoisers exacerbate it -- reconstructing dark pixels up to 6x worse relative to their per-band noise floor. This bias stems from two compounding factors: signal-dependent noise inflates bright-pixel residuals,","authors_text":"Sungjun Cho, Xiaomeng Li, ZhuangZhuang Chen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-15T08:57:38Z","title":"The Devil is in the Dark Pixels: Toward Brightness Bias-Robust Denoising"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.16320","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":"sha256:81341956da81fd3b9aeda8a3b58a3726d9082ca3bae031b31b6c11ca5cc50821","target":"record","created_at":"2026-07-21T00:20:12Z","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":"13f0985821d49c1697b7b07855ce1b9e962b69a30d40570c225917c108a67801","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-15T08:57:38Z","title_canon_sha256":"344f15e8d8bb8e3729d98a61ced7eff52a9cd06a4a4268f6e93acdb9ef5fe29f"},"schema_version":"1.0","source":{"id":"2607.16320","kind":"arxiv","version":1}},"canonical_sha256":"71755ba6b872fe74ef072aa12dfdce4ffc65284facef07ae7f5392235a97ce32","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"71755ba6b872fe74ef072aa12dfdce4ffc65284facef07ae7f5392235a97ce32","first_computed_at":"2026-07-21T00:20:12.118411Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-21T00:20:12.118411Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tJhOwRhdfLCbA/+CjoDFKvs7tX55U7IIN8AQCirHKfw1mFRW3ULzVz6N328pnd65a2qHqXsuSTXfTwcxPVxcDQ==","signature_status":"signed_v1","signed_at":"2026-07-21T00:20:12.119395Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.16320","source_kind":"arxiv","source_version":1}}},"equivocations":[{"signer_id":"pith.science","event_type":"integrity_finding","target":"integrity","event_ids":["sha256:0ceeb1b283c0326b9e04998d6e434c328189e8cbd51d3bf62f9e9b34e6c9a71f","sha256:0d84822c51c8dbf0024fde545d07d920c29f682d9e63d59556ac14feea7c9a97","sha256:7db8832d487b16bb3710fc8d78e729b34e0587ae683f35cad9cdcc99b024a24f"]}],"invalid_events":[],"applied_event_ids":["sha256:81341956da81fd3b9aeda8a3b58a3726d9082ca3bae031b31b6c11ca5cc50821","sha256:78da6751e35ca8aa8cdbb0683c6b8fd0b9ac84d4a2e9ffd220bec4f0541c2237"],"state_sha256":"f25d4ed13c1e121d7845c6dad8326eb2716d01aafedcf5cbbd128f2cfd763ec7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UAATBUZTNTcQUapSSb2LQi71EqLMXtR0Hszet1vWglxqCRqSFzteTkzE+cCkhVGq6SDSAAizDkag8ZZriQzUCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T19:51:10.465926Z","bundle_sha256":"bd3cac911a4462dc078d7ef3d79ae5826f425b6ea7961eab778705b23587a2ad"}}