{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:4IUS4LYPPN5BGICQKLKXRMAZ5O","short_pith_number":"pith:4IUS4LYP","canonical_record":{"source":{"id":"2507.18433","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-07-24T14:12:20Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"6cd33d3f15830574db6f49dd555970f302a666b2859497b98f3b6a04f839435a","abstract_canon_sha256":"3bbab2d38ff136d89e1faddb38a80d03276993bbb37078d16a5bab780b0020bd"},"schema_version":"1.0"},"canonical_sha256":"e2292e2f0f7b7a13205052d578b019eba5fff7e8b83bd523966456e3720730ec","source":{"kind":"arxiv","id":"2507.18433","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.18433","created_at":"2026-07-05T11:42:47Z"},{"alias_kind":"arxiv_version","alias_value":"2507.18433v1","created_at":"2026-07-05T11:42:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.18433","created_at":"2026-07-05T11:42:47Z"},{"alias_kind":"pith_short_12","alias_value":"4IUS4LYPPN5B","created_at":"2026-07-05T11:42:47Z"},{"alias_kind":"pith_short_16","alias_value":"4IUS4LYPPN5BGICQ","created_at":"2026-07-05T11:42:47Z"},{"alias_kind":"pith_short_8","alias_value":"4IUS4LYP","created_at":"2026-07-05T11:42:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:4IUS4LYPPN5BGICQKLKXRMAZ5O","target":"record","payload":{"canonical_record":{"source":{"id":"2507.18433","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-07-24T14:12:20Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"6cd33d3f15830574db6f49dd555970f302a666b2859497b98f3b6a04f839435a","abstract_canon_sha256":"3bbab2d38ff136d89e1faddb38a80d03276993bbb37078d16a5bab780b0020bd"},"schema_version":"1.0"},"canonical_sha256":"e2292e2f0f7b7a13205052d578b019eba5fff7e8b83bd523966456e3720730ec","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:42:47.916707Z","signature_b64":"9EK8JE324wTGJypxplVMbA3BFOYOae9ukPhMaVXcJFptDhX4IODyCrOzy/M+Mr43zjms0+bFFLJL9W8pg/UbCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e2292e2f0f7b7a13205052d578b019eba5fff7e8b83bd523966456e3720730ec","last_reissued_at":"2026-07-05T11:42:47.916359Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:42:47.916359Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.18433","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:42:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RXmo9hfsn+sIvEG44nVLiRkuLgZ3Ez6WGYct64Z3V7KXHg/jnX6uAwCZ+LUlbJL0X6+1J4f7Z93NMTLRT1WpCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T14:40:11.421578Z"},"content_sha256":"37fc9e779f8989d7987dace9177ad79557322e361eb42cbb270e3e1c27c67d35","schema_version":"1.0","event_id":"sha256:37fc9e779f8989d7987dace9177ad79557322e361eb42cbb270e3e1c27c67d35"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:4IUS4LYPPN5BGICQKLKXRMAZ5O","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Jiawen Li, Jingli Ouyang, Lianghui Zhu, Li Zheng, Minxi Ouyang, Qiang Huang, Song Duan, Tian Guan, Wenbin Dai, Xitong Ling, Xuemei Zhang, Yaqing Bao, Yonghong He","submitted_at":"2025-07-24T14:12:20Z","abstract_excerpt":"Multimodal large models have shown great potential in automating pathology image analysis. However, current multimodal models for gastrointestinal pathology are constrained by both data quality and reasoning transparency: pervasive noise and incomplete annotations in public datasets predispose vision language models to factual hallucinations when generating diagnostic text, while the absence of explicit intermediate reasoning chains renders the outputs difficult to audit and thus less trustworthy in clinical practice. To address these issues, we construct a large scale gastrointestinal patholo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.18433","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2507.18433/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:42:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vm0MYxqQtJA0nZgaAwr5hBC3nc57VHGKG2QMsM5sftyGGeyDnzFsoRLwFjxBRz38OxNndLMhjYL8RS2EyByjBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T14:40:11.422530Z"},"content_sha256":"358071853f2e01989bd86a2014c33b8f086e5fb58196b41fe3899b59c5d57ce9","schema_version":"1.0","event_id":"sha256:358071853f2e01989bd86a2014c33b8f086e5fb58196b41fe3899b59c5d57ce9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4IUS4LYPPN5BGICQKLKXRMAZ5O/bundle.json","state_url":"https://pith.science/pith/4IUS4LYPPN5BGICQKLKXRMAZ5O/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4IUS4LYPPN5BGICQKLKXRMAZ5O/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-18T14:40:11Z","links":{"resolver":"https://pith.science/pith/4IUS4LYPPN5BGICQKLKXRMAZ5O","bundle":"https://pith.science/pith/4IUS4LYPPN5BGICQKLKXRMAZ5O/bundle.json","state":"https://pith.science/pith/4IUS4LYPPN5BGICQKLKXRMAZ5O/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4IUS4LYPPN5BGICQKLKXRMAZ5O/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4IUS4LYPPN5BGICQKLKXRMAZ5O","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":"3bbab2d38ff136d89e1faddb38a80d03276993bbb37078d16a5bab780b0020bd","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-07-24T14:12:20Z","title_canon_sha256":"6cd33d3f15830574db6f49dd555970f302a666b2859497b98f3b6a04f839435a"},"schema_version":"1.0","source":{"id":"2507.18433","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.18433","created_at":"2026-07-05T11:42:47Z"},{"alias_kind":"arxiv_version","alias_value":"2507.18433v1","created_at":"2026-07-05T11:42:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.18433","created_at":"2026-07-05T11:42:47Z"},{"alias_kind":"pith_short_12","alias_value":"4IUS4LYPPN5B","created_at":"2026-07-05T11:42:47Z"},{"alias_kind":"pith_short_16","alias_value":"4IUS4LYPPN5BGICQ","created_at":"2026-07-05T11:42:47Z"},{"alias_kind":"pith_short_8","alias_value":"4IUS4LYP","created_at":"2026-07-05T11:42:47Z"}],"graph_snapshots":[{"event_id":"sha256:358071853f2e01989bd86a2014c33b8f086e5fb58196b41fe3899b59c5d57ce9","target":"graph","created_at":"2026-07-05T11:42:47Z","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/2507.18433/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multimodal large models have shown great potential in automating pathology image analysis. However, current multimodal models for gastrointestinal pathology are constrained by both data quality and reasoning transparency: pervasive noise and incomplete annotations in public datasets predispose vision language models to factual hallucinations when generating diagnostic text, while the absence of explicit intermediate reasoning chains renders the outputs difficult to audit and thus less trustworthy in clinical practice. To address these issues, we construct a large scale gastrointestinal patholo","authors_text":"Jiawen Li, Jingli Ouyang, Lianghui Zhu, Li Zheng, Minxi Ouyang, Qiang Huang, Song Duan, Tian Guan, Wenbin Dai, Xitong Ling, Xuemei Zhang, Yaqing Bao, Yonghong He","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-07-24T14:12:20Z","title":"DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.18433","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":"sha256:37fc9e779f8989d7987dace9177ad79557322e361eb42cbb270e3e1c27c67d35","target":"record","created_at":"2026-07-05T11:42:47Z","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":"3bbab2d38ff136d89e1faddb38a80d03276993bbb37078d16a5bab780b0020bd","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-07-24T14:12:20Z","title_canon_sha256":"6cd33d3f15830574db6f49dd555970f302a666b2859497b98f3b6a04f839435a"},"schema_version":"1.0","source":{"id":"2507.18433","kind":"arxiv","version":1}},"canonical_sha256":"e2292e2f0f7b7a13205052d578b019eba5fff7e8b83bd523966456e3720730ec","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e2292e2f0f7b7a13205052d578b019eba5fff7e8b83bd523966456e3720730ec","first_computed_at":"2026-07-05T11:42:47.916359Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:42:47.916359Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9EK8JE324wTGJypxplVMbA3BFOYOae9ukPhMaVXcJFptDhX4IODyCrOzy/M+Mr43zjms0+bFFLJL9W8pg/UbCw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:42:47.916707Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.18433","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:37fc9e779f8989d7987dace9177ad79557322e361eb42cbb270e3e1c27c67d35","sha256:358071853f2e01989bd86a2014c33b8f086e5fb58196b41fe3899b59c5d57ce9"],"state_sha256":"1a6eacdb6fe4bf02cd8b1eec12c47329eeb42047e9020e161fd06f4f2567dedc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Dkz+SVuHq0FRbz78h0R6JVPz414rLJyRS4RN51KlFB4B3RCny1Xb2a2legcE7nTO1VKbxfmcHrgqvQWv7DkqBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T14:40:11.432306Z","bundle_sha256":"8098e760a3cc462b3b090979dd23dba39ae9e8c4bd328cc2497e82957e9b24bf"}}