{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:D3G5BJ5L5FBMJ2YEH32RCRJX5A","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":"9ff2eadc80ccac0a563a810bf1c5aceed1d4d27c89e85fdb196eae9e7fce874b","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-03T14:17:57Z","title_canon_sha256":"8517c677940143ad25a94323c86d98d7a4d58eeb69dfe440358ccebace6ac8c7"},"schema_version":"1.0","source":{"id":"2606.04922","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.04922","created_at":"2026-06-04T01:09:55Z"},{"alias_kind":"arxiv_version","alias_value":"2606.04922v1","created_at":"2026-06-04T01:09:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.04922","created_at":"2026-06-04T01:09:55Z"},{"alias_kind":"pith_short_12","alias_value":"D3G5BJ5L5FBM","created_at":"2026-06-04T01:09:55Z"},{"alias_kind":"pith_short_16","alias_value":"D3G5BJ5L5FBMJ2YE","created_at":"2026-06-04T01:09:55Z"},{"alias_kind":"pith_short_8","alias_value":"D3G5BJ5L","created_at":"2026-06-04T01:09:55Z"}],"graph_snapshots":[{"event_id":"sha256:539166ba29eda500c2ea173ce45bec435a18798f16ec7dcfb7550e17ba3376c9","target":"graph","created_at":"2026-06-04T01:09:55Z","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/2606.04922/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Current prompt-based and adapter-based tuning of vision-language models (VLMs) is attractive for medical imaging, where clinical data sensitivity favors frozen backbones and annotations are limited. However, these methods typically optimize only the ground-truth class, treating all other classes as equally incorrect, ignoring clinically meaningful class relations and yielding unstable decision boundaries in limited-supervision settings. We propose Omni-Geometry Knowledge Distillation (OGKD), a new framework that injects class-relation structure into the teacher to produce directional targets t","authors_text":"Tran Dinh Tien, Zhiqiang Shen","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-03T14:17:57Z","title":"Geometry-Aware Distillation for Prompt Tuning Biomedical Vision-Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.04922","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":"sha256:8c92e7770b4b19033e74ddc59e2551d90b633789b9af011754968663755fcedd","target":"record","created_at":"2026-06-04T01:09:55Z","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":"9ff2eadc80ccac0a563a810bf1c5aceed1d4d27c89e85fdb196eae9e7fce874b","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-03T14:17:57Z","title_canon_sha256":"8517c677940143ad25a94323c86d98d7a4d58eeb69dfe440358ccebace6ac8c7"},"schema_version":"1.0","source":{"id":"2606.04922","kind":"arxiv","version":1}},"canonical_sha256":"1ecdd0a7abe942c4eb043ef5114537e802e1560d5e9cf3beaab9e495ee9168fd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1ecdd0a7abe942c4eb043ef5114537e802e1560d5e9cf3beaab9e495ee9168fd","first_computed_at":"2026-06-04T01:09:55.792028Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-04T01:09:55.792028Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vG3yFmIjl2V46mD+qReu3ICyAL7cGzVa6Uu9H/ADRO5sow5PCRTgyY70tFOdD+cX9FYn6PGP4Ptb+s7MWbtrBw==","signature_status":"signed_v1","signed_at":"2026-06-04T01:09:55.792652Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.04922","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8c92e7770b4b19033e74ddc59e2551d90b633789b9af011754968663755fcedd","sha256:539166ba29eda500c2ea173ce45bec435a18798f16ec7dcfb7550e17ba3376c9"],"state_sha256":"7b7b2876d17f795dc330d496b943a8b24cee46801e92115d604e095432147fa5"}