{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:P526E27GJ2EZBFGSDKZH463AGW","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":"5fb3d3fbeb6027f7c0b2cae7cc2b8558dfd790a920352a8aed0fbe953352f714","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-07-03T09:20:28Z","title_canon_sha256":"83c9bc6b67af9a22ef880a3e303f4d3d485e26c6984676a7014e8f9882978c05"},"schema_version":"1.0","source":{"id":"2307.00880","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.00880","created_at":"2026-07-05T06:27:01Z"},{"alias_kind":"arxiv_version","alias_value":"2307.00880v1","created_at":"2026-07-05T06:27:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.00880","created_at":"2026-07-05T06:27:01Z"},{"alias_kind":"pith_short_12","alias_value":"P526E27GJ2EZ","created_at":"2026-07-05T06:27:01Z"},{"alias_kind":"pith_short_16","alias_value":"P526E27GJ2EZBFGS","created_at":"2026-07-05T06:27:01Z"},{"alias_kind":"pith_short_8","alias_value":"P526E27G","created_at":"2026-07-05T06:27:01Z"}],"graph_snapshots":[{"event_id":"sha256:eb46be3e379eb049677548c69f597ab2c2bf78032a28d8d9015c7def90e48fca","target":"graph","created_at":"2026-07-05T06:27:01Z","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/2307.00880/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In real-world scenarios, collected and annotated data often exhibit the characteristics of multiple classes and long-tailed distribution. Additionally, label noise is inevitable in large-scale annotations and hinders the applications of learning-based models. Although many deep learning based methods have been proposed for handling long-tailed multi-label recognition or label noise respectively, learning with noisy labels in long-tailed multi-label visual data has not been well-studied because of the complexity of long-tailed distribution entangled with multi-label correlation. To tackle such ","authors_text":"Chao Liang, Linchao Zhu, Yi Yang, Zongxin Yang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-07-03T09:20:28Z","title":"Co-Learning Meets Stitch-Up for Noisy Multi-label Visual Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.00880","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":"sha256:40f810939c207c942c7198ca10a6dcaae4855dfb89d37fec2a0714dd9b10e349","target":"record","created_at":"2026-07-05T06:27:01Z","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":"5fb3d3fbeb6027f7c0b2cae7cc2b8558dfd790a920352a8aed0fbe953352f714","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-07-03T09:20:28Z","title_canon_sha256":"83c9bc6b67af9a22ef880a3e303f4d3d485e26c6984676a7014e8f9882978c05"},"schema_version":"1.0","source":{"id":"2307.00880","kind":"arxiv","version":1}},"canonical_sha256":"7f75e26be64e899094d21ab27e7b6035bb659d37e3344c66e57eb990736bc738","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7f75e26be64e899094d21ab27e7b6035bb659d37e3344c66e57eb990736bc738","first_computed_at":"2026-07-05T06:27:01.482552Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:27:01.482552Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"95lBXjFHVeK5IELuCkVyX7GpvtFP7RMo+hFVVkaSDcUeEiAHUpGEoH4yGrDOsoNgt8gJZf3GoQaik+lcID7lBg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:27:01.483016Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.00880","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:40f810939c207c942c7198ca10a6dcaae4855dfb89d37fec2a0714dd9b10e349","sha256:eb46be3e379eb049677548c69f597ab2c2bf78032a28d8d9015c7def90e48fca"],"state_sha256":"2b75f242122f58720c5a88bcf93bb086514fab95fa1fe7ba473c27c2a6d41a21"}