{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:3SBPJNWSPZG475TAMYPIUZCZI5","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":"f08354ae442f9d8ea47c6f2eaccada8dcc060a41073f80b1eb5a260b13e2ed5f","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-10T08:09:21Z","title_canon_sha256":"009448075324f44b62a7731e04d03d062f173f8b86f4befc1a51c34ad64a7217"},"schema_version":"1.0","source":{"id":"2203.05956","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.05956","created_at":"2026-07-05T04:04:11Z"},{"alias_kind":"arxiv_version","alias_value":"2203.05956v1","created_at":"2026-07-05T04:04:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.05956","created_at":"2026-07-05T04:04:11Z"},{"alias_kind":"pith_short_12","alias_value":"3SBPJNWSPZG4","created_at":"2026-07-05T04:04:11Z"},{"alias_kind":"pith_short_16","alias_value":"3SBPJNWSPZG475TA","created_at":"2026-07-05T04:04:11Z"},{"alias_kind":"pith_short_8","alias_value":"3SBPJNWS","created_at":"2026-07-05T04:04:11Z"}],"graph_snapshots":[{"event_id":"sha256:120f56fee224496ca7e04f8f3c888e7de506d8e0c82356b3288634659e2fab0e","target":"graph","created_at":"2026-07-05T04:04:11Z","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/2203.05956/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Due to the lack of expertise for medical image annotation, the investigation of label-efficient methodology for medical image segmentation becomes a heated topic. Recent progresses focus on the efficient utilization of weak annotations together with few strongly-annotated labels so as to achieve comparable segmentation performance in many unprofessional scenarios. However, these approaches only concentrate on the supervision inconsistency between strongly- and weakly-annotated instances but ignore the instance inconsistency inside the weakly-annotated instances, which inevitably leads to perfo","authors_text":"Cheng Bian, Junwen Pan, Pengfei Zhu, Qi Bi, Yanzhan Yang","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-10T08:09:21Z","title":"Label-efficient Hybrid-supervised Learning for Medical Image Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.05956","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":"sha256:2b8f745590288196731d7eaf4ab82c86d8dc27acd93e7d358b370116006a6f94","target":"record","created_at":"2026-07-05T04:04:11Z","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":"f08354ae442f9d8ea47c6f2eaccada8dcc060a41073f80b1eb5a260b13e2ed5f","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-10T08:09:21Z","title_canon_sha256":"009448075324f44b62a7731e04d03d062f173f8b86f4befc1a51c34ad64a7217"},"schema_version":"1.0","source":{"id":"2203.05956","kind":"arxiv","version":1}},"canonical_sha256":"dc82f4b6d27e4dcff660661e8a6459477d36a1086d2a35b36ea93b85fb7e7caf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dc82f4b6d27e4dcff660661e8a6459477d36a1086d2a35b36ea93b85fb7e7caf","first_computed_at":"2026-07-05T04:04:11.260434Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:04:11.260434Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"psUdgylyvh4EK+FH23wKsbFyIgDTG3Qwe3raLTD+jXWwfKq8ZmPHCjrXvSkmQieF9X1zf06ldcFuIGzK7TpEAA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:04:11.260858Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.05956","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2b8f745590288196731d7eaf4ab82c86d8dc27acd93e7d358b370116006a6f94","sha256:120f56fee224496ca7e04f8f3c888e7de506d8e0c82356b3288634659e2fab0e"],"state_sha256":"99f3a42d1f894b550e9cd642b6404541933d26dce3e04105480f8b2a623e7b0c"}