{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:744M2RC2MTQ3RABEDZLOWS2ZTN","short_pith_number":"pith:744M2RC2","canonical_record":{"source":{"id":"2303.09101","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T06:14:18Z","cross_cats_sorted":[],"title_canon_sha256":"e24885d9dd2f2df48270856a0157cb4ada5baef5c3e1ecd65df630db27797fd2","abstract_canon_sha256":"d20964ed7eb376082cabb7c29f678c2fd9f7265bb6b5cb4b54059e17f7599772"},"schema_version":"1.0"},"canonical_sha256":"ff38cd445a64e1b880241e56eb4b599b6bc2bd4b171d815b25043fbb6040350d","source":{"kind":"arxiv","id":"2303.09101","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.09101","created_at":"2026-07-05T05:57:36Z"},{"alias_kind":"arxiv_version","alias_value":"2303.09101v4","created_at":"2026-07-05T05:57:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.09101","created_at":"2026-07-05T05:57:36Z"},{"alias_kind":"pith_short_12","alias_value":"744M2RC2MTQ3","created_at":"2026-07-05T05:57:36Z"},{"alias_kind":"pith_short_16","alias_value":"744M2RC2MTQ3RABE","created_at":"2026-07-05T05:57:36Z"},{"alias_kind":"pith_short_8","alias_value":"744M2RC2","created_at":"2026-07-05T05:57:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:744M2RC2MTQ3RABEDZLOWS2ZTN","target":"record","payload":{"canonical_record":{"source":{"id":"2303.09101","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T06:14:18Z","cross_cats_sorted":[],"title_canon_sha256":"e24885d9dd2f2df48270856a0157cb4ada5baef5c3e1ecd65df630db27797fd2","abstract_canon_sha256":"d20964ed7eb376082cabb7c29f678c2fd9f7265bb6b5cb4b54059e17f7599772"},"schema_version":"1.0"},"canonical_sha256":"ff38cd445a64e1b880241e56eb4b599b6bc2bd4b171d815b25043fbb6040350d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:57:36.463926Z","signature_b64":"ufwuUoYqXnpm8VIgiIP7tvx9REQA3cHV2pyran1XWGjCKjGMZ4OHkIxu3GZW21bWSr00umAmnYPlmbsdphKeCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ff38cd445a64e1b880241e56eb4b599b6bc2bd4b171d815b25043fbb6040350d","last_reissued_at":"2026-07-05T05:57:36.463427Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:57:36.463427Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2303.09101","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:57:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"atVyvTJelWZKlmIunhcryxDEWa+VhDrIykuUuV3j3ujpBLCc9qz8lQOnj4YbENNUuxgm/M+NpqwzlsOVzckMDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T06:50:37.208079Z"},"content_sha256":"676ca789e3007fe973a1efc23f507f9e88f4bc7aca0fc86ecf05f4ab39492674","schema_version":"1.0","event_id":"sha256:676ca789e3007fe973a1efc23f507f9e88f4bc7aca0fc86ecf05f4ab39492674"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:744M2RC2MTQ3RABEDZLOWS2ZTN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Contrastive Semi-supervised Learning for Underwater Image Restoration via Reliable Bank","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Huan Liu, Jun Chen, Keyan Wang, Shirui Huang, Yunsong Li","submitted_at":"2023-03-16T06:14:18Z","abstract_excerpt":"Despite the remarkable achievement of recent underwater image restoration techniques, the lack of labeled data has become a major hurdle for further progress. In this work, we propose a mean-teacher based Semi-supervised Underwater Image Restoration (Semi-UIR) framework to incorporate the unlabeled data into network training. However, the naive mean-teacher method suffers from two main problems: (1) The consistency loss used in training might become ineffective when the teacher's prediction is wrong. (2) Using L1 distance may cause the network to overfit wrong labels, resulting in confirmation"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.09101","kind":"arxiv","version":4},"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/2303.09101/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":"2026-07-05T05:57:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YdVSC3ci1o05tNOWTIttXJ6DN5DR/t5iTVET7DQEWu8fTHjkxAgHoSHOuVLXjJ23uino8hU9iquHO7Zr1I2eBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T06:50:37.208574Z"},"content_sha256":"e4fad4c77837f10b8636c04a1171c2372d1a00f83b2276bd1dab070dc4d5766f","schema_version":"1.0","event_id":"sha256:e4fad4c77837f10b8636c04a1171c2372d1a00f83b2276bd1dab070dc4d5766f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/744M2RC2MTQ3RABEDZLOWS2ZTN/bundle.json","state_url":"https://pith.science/pith/744M2RC2MTQ3RABEDZLOWS2ZTN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/744M2RC2MTQ3RABEDZLOWS2ZTN/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":"2026-08-11T06:50:37Z","links":{"resolver":"https://pith.science/pith/744M2RC2MTQ3RABEDZLOWS2ZTN","bundle":"https://pith.science/pith/744M2RC2MTQ3RABEDZLOWS2ZTN/bundle.json","state":"https://pith.science/pith/744M2RC2MTQ3RABEDZLOWS2ZTN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/744M2RC2MTQ3RABEDZLOWS2ZTN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:744M2RC2MTQ3RABEDZLOWS2ZTN","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":"d20964ed7eb376082cabb7c29f678c2fd9f7265bb6b5cb4b54059e17f7599772","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T06:14:18Z","title_canon_sha256":"e24885d9dd2f2df48270856a0157cb4ada5baef5c3e1ecd65df630db27797fd2"},"schema_version":"1.0","source":{"id":"2303.09101","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.09101","created_at":"2026-07-05T05:57:36Z"},{"alias_kind":"arxiv_version","alias_value":"2303.09101v4","created_at":"2026-07-05T05:57:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.09101","created_at":"2026-07-05T05:57:36Z"},{"alias_kind":"pith_short_12","alias_value":"744M2RC2MTQ3","created_at":"2026-07-05T05:57:36Z"},{"alias_kind":"pith_short_16","alias_value":"744M2RC2MTQ3RABE","created_at":"2026-07-05T05:57:36Z"},{"alias_kind":"pith_short_8","alias_value":"744M2RC2","created_at":"2026-07-05T05:57:36Z"}],"graph_snapshots":[{"event_id":"sha256:e4fad4c77837f10b8636c04a1171c2372d1a00f83b2276bd1dab070dc4d5766f","target":"graph","created_at":"2026-07-05T05:57:36Z","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/2303.09101/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Despite the remarkable achievement of recent underwater image restoration techniques, the lack of labeled data has become a major hurdle for further progress. In this work, we propose a mean-teacher based Semi-supervised Underwater Image Restoration (Semi-UIR) framework to incorporate the unlabeled data into network training. However, the naive mean-teacher method suffers from two main problems: (1) The consistency loss used in training might become ineffective when the teacher's prediction is wrong. (2) Using L1 distance may cause the network to overfit wrong labels, resulting in confirmation","authors_text":"Huan Liu, Jun Chen, Keyan Wang, Shirui Huang, Yunsong Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T06:14:18Z","title":"Contrastive Semi-supervised Learning for Underwater Image Restoration via Reliable Bank"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.09101","kind":"arxiv","version":4},"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":"sha256:676ca789e3007fe973a1efc23f507f9e88f4bc7aca0fc86ecf05f4ab39492674","target":"record","created_at":"2026-07-05T05:57:36Z","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":"d20964ed7eb376082cabb7c29f678c2fd9f7265bb6b5cb4b54059e17f7599772","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T06:14:18Z","title_canon_sha256":"e24885d9dd2f2df48270856a0157cb4ada5baef5c3e1ecd65df630db27797fd2"},"schema_version":"1.0","source":{"id":"2303.09101","kind":"arxiv","version":4}},"canonical_sha256":"ff38cd445a64e1b880241e56eb4b599b6bc2bd4b171d815b25043fbb6040350d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ff38cd445a64e1b880241e56eb4b599b6bc2bd4b171d815b25043fbb6040350d","first_computed_at":"2026-07-05T05:57:36.463427Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:57:36.463427Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ufwuUoYqXnpm8VIgiIP7tvx9REQA3cHV2pyran1XWGjCKjGMZ4OHkIxu3GZW21bWSr00umAmnYPlmbsdphKeCw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:57:36.463926Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.09101","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:676ca789e3007fe973a1efc23f507f9e88f4bc7aca0fc86ecf05f4ab39492674","sha256:e4fad4c77837f10b8636c04a1171c2372d1a00f83b2276bd1dab070dc4d5766f"],"state_sha256":"0323aa706a0b046719b9b3459fec9aa9b73739f097836d0c9c8c7ae5cb8cd343"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4N9kMNKTY7MJahO1XpNNTwb0+HuX5oOHpLqXHW1dKPm5mk81rPPbC33qcQhnMHWIaKGGbU4m6KvIADc5qS9FAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T06:50:37.213399Z","bundle_sha256":"38afac9cd57573fc6163cf2b10a64b7b06d19eef3866e675d84b6a724c54225a"}}