{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:EB4N25U45ZKXMBHS7GXW3ZCRWW","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":"fd9c627a05c61bec64abcd283a3eb87eb08ea000e275ea70b6c2d0eeb92efb49","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-27T05:49:06Z","title_canon_sha256":"681d09dcca3b713ad44e94ddab7b16a3682e4e024ceb745f5cb95a7c7d7d01fd"},"schema_version":"1.0","source":{"id":"2501.15798","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.15798","created_at":"2026-07-05T11:57:54Z"},{"alias_kind":"arxiv_version","alias_value":"2501.15798v1","created_at":"2026-07-05T11:57:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.15798","created_at":"2026-07-05T11:57:54Z"},{"alias_kind":"pith_short_12","alias_value":"EB4N25U45ZKX","created_at":"2026-07-05T11:57:54Z"},{"alias_kind":"pith_short_16","alias_value":"EB4N25U45ZKXMBHS","created_at":"2026-07-05T11:57:54Z"},{"alias_kind":"pith_short_8","alias_value":"EB4N25U4","created_at":"2026-07-05T11:57:54Z"}],"graph_snapshots":[{"event_id":"sha256:c4b6a426f65255960cdec7f5071303e6219f8d3f240ac15a59439e4f22e78f55","target":"graph","created_at":"2026-07-05T11:57:54Z","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/2501.15798/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vision-language pretraining (VLP) has been investigated to generalize across diverse downstream tasks for fundus image analysis. Although recent methods showcase promising achievements, they significantly rely on large-scale private image-text data but pay less attention to the pretraining manner, which limits their further advancements. In this work, we introduce MM-Retinal V2, a high-quality image-text paired dataset comprising CFP, FFA, and OCT image modalities. Then, we propose a novel fundus vision-language pretraining model, namely KeepFIT V2, which is pretrained by integrating knowledge","authors_text":"Chenran Zhang, Huazhu Fu, Na Su, Nianfeng Tang, Ruiqi Wu, Shenqi Jing, Tao Zhou, Tengfei Ma, Tianxing Wu, Tianyu Mao, Wen Fan, Yi Zhou, Zhiting Cui","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-27T05:49:06Z","title":"MM-Retinal V2: Transfer an Elite Knowledge Spark into Fundus Vision-Language Pretraining"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.15798","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:d5c0d70ca3b23dd772722787d0d4cfefcb0d70d9de077934236ce7f13a02cbb4","target":"record","created_at":"2026-07-05T11:57:54Z","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":"fd9c627a05c61bec64abcd283a3eb87eb08ea000e275ea70b6c2d0eeb92efb49","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-27T05:49:06Z","title_canon_sha256":"681d09dcca3b713ad44e94ddab7b16a3682e4e024ceb745f5cb95a7c7d7d01fd"},"schema_version":"1.0","source":{"id":"2501.15798","kind":"arxiv","version":1}},"canonical_sha256":"2078dd769cee557604f2f9af6de451b59e021c08edc3dd1a143211eb1748670e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2078dd769cee557604f2f9af6de451b59e021c08edc3dd1a143211eb1748670e","first_computed_at":"2026-07-05T11:57:54.542094Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:57:54.542094Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/aoeH0XBj89PT0fDJOkFRfZ7X+7b7Z3pPO3MiNg60t0vvxJw/WfIgHlq5jbCdS3C2+SRIbXLsrxz4ZmXCWT7BA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:57:54.542576Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.15798","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d5c0d70ca3b23dd772722787d0d4cfefcb0d70d9de077934236ce7f13a02cbb4","sha256:c4b6a426f65255960cdec7f5071303e6219f8d3f240ac15a59439e4f22e78f55"],"state_sha256":"ef5aec5f1bedf123c545f842b42de00a8f285bcfa06a5a9ec6ca8d407f01166a"}