{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ADNY6YJ7BOIBH3KAC5KFIRT7WF","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":"04f14e2f030213880c2d7476c907632c554a2e105c4fced507152343ca5a5d7c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-11T07:18:01Z","title_canon_sha256":"dc6f00152a847dfdd3a68e6154190a04a5b102e345ae351713e461f93fca6ff9"},"schema_version":"1.0","source":{"id":"2507.08357","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.08357","created_at":"2026-07-05T11:35:21Z"},{"alias_kind":"arxiv_version","alias_value":"2507.08357v1","created_at":"2026-07-05T11:35:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.08357","created_at":"2026-07-05T11:35:21Z"},{"alias_kind":"pith_short_12","alias_value":"ADNY6YJ7BOIB","created_at":"2026-07-05T11:35:21Z"},{"alias_kind":"pith_short_16","alias_value":"ADNY6YJ7BOIBH3KA","created_at":"2026-07-05T11:35:21Z"},{"alias_kind":"pith_short_8","alias_value":"ADNY6YJ7","created_at":"2026-07-05T11:35:21Z"}],"graph_snapshots":[{"event_id":"sha256:0d55484daec388a5783613a0356f8ed2f35373220629763051f3958bea735648","target":"graph","created_at":"2026-07-05T11:35:21Z","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/2507.08357/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In-context learning (ICL) is emerging as a promising technique for achieving universal medical image segmentation, where a variety of objects of interest across imaging modalities can be segmented using a single model. Nevertheless, its performance is highly sensitive to the alignment between the query image and in-context image-mask pairs. In a clinical scenario, the scarcity of annotated medical images makes it challenging to select optimal in-context pairs, and fine-tuning foundation ICL models on contextual data is infeasible due to computational costs and the risk of catastrophic forgetti","authors_text":"Huazhu Fu, Liangli Zhen, Shishuai Hu, Yong Xia, Zehui Liao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-11T07:18:01Z","title":"Cycle Context Verification for In-Context Medical Image Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.08357","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:e0b14644d5d4a373d84eabfd33d91f1581c7e657ecb0652f88aa1b9d3484532c","target":"record","created_at":"2026-07-05T11:35:21Z","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":"04f14e2f030213880c2d7476c907632c554a2e105c4fced507152343ca5a5d7c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-11T07:18:01Z","title_canon_sha256":"dc6f00152a847dfdd3a68e6154190a04a5b102e345ae351713e461f93fca6ff9"},"schema_version":"1.0","source":{"id":"2507.08357","kind":"arxiv","version":1}},"canonical_sha256":"00db8f613f0b9013ed40175454467fb14bbb155610a76567048c0499ba332485","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"00db8f613f0b9013ed40175454467fb14bbb155610a76567048c0499ba332485","first_computed_at":"2026-07-05T11:35:21.922918Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:35:21.922918Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aAtCaJOKLaPQdoP1j4Y2AFpPjNOmJijfNyz7G4cYNjz23hZLiaAt0uwSpPoyhDaXKSKYJelhUc9FazFvnHGoDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:35:21.923415Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.08357","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e0b14644d5d4a373d84eabfd33d91f1581c7e657ecb0652f88aa1b9d3484532c","sha256:0d55484daec388a5783613a0356f8ed2f35373220629763051f3958bea735648"],"state_sha256":"f2da3b2acbbb296a4e9506da9d0ff658e132b8be76016060144d7d9f9b7f231a"}