{"as_of":"2026-08-07T18:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4802eca4206247fad936a28577ce0f362dd092a4fe2892e09524a0e4374b3ae6","coverage":[{"denominator":60,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":60,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T10:46:09.996574Z","state":"measured"},{"denominator":62,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":62,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T19:34:04.544567Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-06-28T19:22:34.657932Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.03800","snapshot_observed_at":"2026-08-03T19:34:04.544567Z","title":"Med- vista3d: Vision-language modeling for reducing diagnostic errors in 3d ct disease detection, un- derstanding and reporting.arXiv preprint arXiv:2509.03800, 2025b","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.00239","last_updated":"2026-06-07T22:52:48Z","snapshot_observed_at":"2026-08-03T19:34:03.096776Z","submitted_at":"2025-11-28T22:53:31Z","title":"Self-Supervised Dynamical System Representations for Physiological Time-Series","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T19:34:04.544567Z"},"links":{"cited_paper":"/paper/2509.03800","citing_paper":"/paper/2512.00239"},"observation_digest":"sha256:b9e678fc66757ae5d71926e25a394ba0236af21004801cda7a6c33f0ce079ae9","observation_id":"0cd03453-c97c-4b33-9b7c-1d3daeea6f74","resolution":{"observed_at":"2026-08-03T19:34:04.544567Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"cited_work":{"arxiv_id":"2509.03800","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2509.03800","snapshot_observed_at":"2026-06-28T19:22:34.657932Z","title":"Medvista3d: Vision-language modeling for reducing diagnostic errors in 3d ct disease detection, understanding and reporting,","venue":null,"work_id":"a5511f07-ba18-4865-b330-19daca5fc28e","year":2025},"citing_paper":{"arxiv_id":"2606.00602","last_updated":"2026-05-30T07:59:21Z","snapshot_observed_at":"2026-07-06T23:41:15.410587Z","submitted_at":"2026-05-30T07:59:21Z","title":"ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-06-28T19:16:42.139096Z"},"links":{"cited_paper":"/paper/2509.03800","citing_paper":"/paper/2606.00602"},"observation_digest":"sha256:7de417b13444d2a1810da87e18e48b1a92b9b4b68dd0d4444f32c9b3fd51d905","observation_id":"e8ecbf8a-69eb-48e9-9d43-16ea5263acd2","resolution":{"observed_at":"2026-06-28T19:22:34.659378Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2509.03800/citation-record","integrity":"/paper/2509.03800/integrity","json":"/paper/2509.03800/citation-record.json","paper":"/paper/2509.03800"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:04.243549Z","title":"Merlin: A vision language foundation model for 3d computed tomography","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:04.243549Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:72fa11f8830f5b82beb81d8549065cd7d0901e5dc6d0c6287dd32cd376333264","observation_id":"a6fa80d1-f5d6-4f4a-8c11-f7590af040bf","resolution":{"observed_at":"2026-08-05T10:46:04.243549Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.953946Z","title":"A vision–language foundation model for the generation of realistic chest x-ray images","venue":null,"work_id":"8cf289c1-4b0b-493a-bf6b-56c20d411669","year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:04.330865Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:569ca31b82ce1a8bdc7e5f52ae7f99e8e77cb5ad1ec3a77ddce4dcf190a432a7","observation_id":"b33a7ab9-9f9f-45d3-8445-97b33ff2b16b","resolution":{"observed_at":"2026-08-05T10:46:13.958572Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:04.426003Z","title":"Making the most of text semantics to improve biomedical vision–language processing","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:04.426003Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:16316adc192f52129915266b6d1cabb503505116588039e4128a9b302865fe43","observation_id":"cb37fff5-0668-4885-9707-e0ec24f3015e","resolution":{"observed_at":"2026-08-05T10:46:04.426003Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.928235Z","title":"Understanding and confronting our mis- takes: the epidemiology of error in radiology and strategies for error reduction","venue":null,"work_id":"584728aa-0d65-4a74-bd77-8eba9d20f6ca","year":2015},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:04.516487Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:ec32d44d4c05a504591cb5facc99da9ff1c590dca8cd9d83321d9ef23a9c2595","observation_id":"d404663f-9670-4008-8297-2b334af143b6","resolution":{"observed_at":"2026-08-05T10:46:13.932829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.913157Z","title":"Joint modeling of chest radiographs and radiology reports for pulmonary edema assessment","venue":null,"work_id":"baa2c859-63e5-4a43-a813-e46720f487b5","year":2020},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:04.585735Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:fe3dee927d0b94f8388fabb7a5abbfd4d224391ef6deac390b381ec46aae2e6e","observation_id":"c143d303-e11e-4e10-bd16-89cf43f4e210","resolution":{"observed_at":"2026-08-05T10:46:13.917747Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02746","last_updated":"2025-02-19T05:59:59Z","snapshot_observed_at":"2026-08-06T15:05:24.928841Z","submitted_at":"2024-10-03T17:56:09Z","title":"Contrastive Localized Language-Image Pre-Training","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02746","snapshot_observed_at":"2026-08-05T10:46:04.661105Z","title":"Contrastive localized language-image pre-training","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:04.661105Z"},"links":{"cited_paper":"/paper/2410.02746","citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:436fd92b0532fd11ea56fd94ffdddab7422f23acbbc42a8dec8ee285db120d48","observation_id":"41ed5110-7327-4e3d-bafa-1a1622ef2ee5","resolution":{"observed_at":"2026-08-05T10:46:04.661105Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.895688Z","title":"A review of medical image data augmentation techniques for deep learning applications","venue":null,"work_id":"59f8838b-2c39-4eca-9c72-80287a5e5307","year":2021},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:04.776379Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:fcf7db3518904b044201edd3495361105c43017f1d488798213010a917913504","observation_id":"3f111173-6cf8-4d07-8f39-b1d2c4ddf619","resolution":{"observed_at":"2026-08-05T10:46:13.900852Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.879928Z","title":"Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes","venue":null,"work_id":"2744172b-bf54-4156-84db-79b78d5a2cec","year":2021},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:04.842478Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:475afe3458acbf4e7c8fc166185cc59cf83a595be09d1cf68ffb2fe81713eaaf","observation_id":"f555adc7-97f4-414c-8a7b-5d9ba7d8b2d8","resolution":{"observed_at":"2026-08-05T10:46:13.884634Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.18119","last_updated":"2025-03-27T17:39:55Z","snapshot_observed_at":"2026-08-04T02:52:45.287213Z","submitted_at":"2024-09-26T17:56:59Z","title":"Multi-View and Multi-Scale Alignment for Contrastive Language-Image Pre-training in Mammography","version":2},"cited_work":{"arxiv_id":"2409.18119","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.18119","snapshot_observed_at":"2026-08-05T10:46:10.496135Z","title":"Multi-View and Multi-Scale Alignment for Contrastive Language-Image Pre-training in Mammography","venue":"cs.CV","work_id":"7036e351-8912-414c-b2e1-a1749a2788ed","year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:04.962958Z"},"links":{"cited_paper":"/paper/2409.18119","citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:136227593cd3536be2ebb02df1e5cd4ad54dbb3bbdc818422a03eec93a0e2d6d","observation_id":"85df312c-28df-4027-8a32-0cf6486e38a7","resolution":{"observed_at":"2026-08-05T10:46:10.536952Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-07-06T18:55:11.576666Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-05T10:46:05.092590Z","title":"The llama 3 herd of models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:05.092590Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:a913edd078b6cb4a5e86d2344bcd8876b4a32e3177c2c77d5c9fd245b58e43ef","observation_id":"4feab371-5592-4901-b37e-221704c40765","resolution":{"observed_at":"2026-08-05T10:46:05.092590Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:05.191575Z","title":"Devel- oping generalist foundation models from a multimodal dataset for 3d computed tomography","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:05.191575Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:2cb76af8c525d5b12b3378de30af39e5d237c3d0c86f7c996f2e51df93f1a747","observation_id":"13ac3f6d-a019-4f0b-825c-d36d7414fa43","resolution":{"observed_at":"2026-08-05T10:46:05.191575Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-07T07:43:16.294957Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-05T10:46:05.296884Z","title":"Lora: Low-rank adaptation of large language models","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:05.296884Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:a7377d1d4610b3c6e92c1b6b4a08f79c4c60343e813e14699a003ad4b0c48c85","observation_id":"ac57e9c6-b566-4905-a756-dd5818e81d92","resolution":{"observed_at":"2026-08-05T10:46:05.296884Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:05.360284Z","title":"Gloria: A multimodal global-local representation learning framework for label-efficient medical image recognition","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:05.360284Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:0af129921b0578143c0f0ae027d1efe21c605145f54d7a5e33f1181d876682c3","observation_id":"aa273c70-1ad5-4176-a12e-25ee2a518a90","resolution":{"observed_at":"2026-08-05T10:46:05.360284Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.854850Z","title":"Enhancing representation in medical vision-language foun- dation models via multi-scale information extraction techniques","venue":null,"work_id":"6c5183a8-1834-492e-b0fa-22df6ac53d04","year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:05.458401Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:97fc38fff9526e5daf74d9ab396c08e0c409ea06e0e7b1d44ad2839d99b5308e","observation_id":"c7bf766a-ec65-41da-a482-156f75f1b8da","resolution":{"observed_at":"2026-08-05T10:46:13.859199Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06716","last_updated":"2023-04-13T17:59:13Z","snapshot_observed_at":"2026-07-06T15:15:26.125395Z","submitted_at":"2023-04-13T17:59:13Z","title":"STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06716","snapshot_observed_at":"2026-08-05T10:46:05.562057Z","title":"Stu-net: Scalable and transferable medical image segmentation models empowered by large-scale supervised pre-training","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:05.562057Z"},"links":{"cited_paper":"/paper/2304.06716","citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:877b3c80a15e2d11135158a395f68bfbd1f36c79f0e5c745abc4c840c5aab4da","observation_id":"da68f205-0616-4a33-8ce2-23eb68858145","resolution":{"observed_at":"2026-08-05T10:46:05.562057Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:05.633725Z","title":"nnu-net: a self-configuring method for deep learning-based biomedical image segmentation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:05.633725Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:3cc8af1f9af61afb361cb8d534c687df0398f88062acb0dadd82e15e19e5ac7c","observation_id":"4dbc9100-63b5-4b79-b258-fb0395cb7c62","resolution":{"observed_at":"2026-08-05T10:46:05.633725Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.829867Z","title":"Fool me twice: delayed diagnoses in radiology with emphasis on perpetuated errors","venue":null,"work_id":"5ac2cad2-9f58-4daf-b0d0-96acdc72e4db","year":2014},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:05.740237Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:6aa827fcef7848e6c2eb05b32ab95d26f030a1288981e61ab831445be7c8c116","observation_id":"0d20a01c-58e5-4de6-8e64-28d7416906b8","resolution":{"observed_at":"2026-08-05T10:46:13.834498Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.814701Z","title":"Generating synthetic data for medical imaging","venue":null,"work_id":"6a6a4511-5c64-4ea1-8fd3-313176e39656","year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:05.837515Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:d67bf2a06f83c2fc31f668715a508057020b98e9aee817e72efbfe932fa10d5e","observation_id":"0ef9eb6e-3c40-4f58-8234-d3ac1161d8f4","resolution":{"observed_at":"2026-08-05T10:46:13.819212Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.798105Z","title":"Cxr-llava: a multimodal large language model for interpreting chest x-ray images","venue":null,"work_id":"7baf51ef-361b-40f1-b2b3-1554bcc5c872","year":2025},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:05.952126Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:94d91d3049d80b7cb4e88e482c26870fd55186c6440527f9b16b6352ceb34f2d","observation_id":"35d0a13e-01ef-4672-bf63-cc177925cee6","resolution":{"observed_at":"2026-08-05T10:46:13.803136Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:06.026153Z","title":"Llava-med: Training a large language-and-vision assistant for biomedicine in one day","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:06.026153Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:7ccc36992eee25d94a0371009013a8a1505ca3a72d418efe8ee38a5400b3ce7f","observation_id":"71cb91cd-edae-46b0-9c62-195ae4964bf7","resolution":{"observed_at":"2026-08-05T10:46:06.026153Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.770165Z","title":"Artificial general intelligence for medical imaging analysis","venue":null,"work_id":"d74d2bbf-6de1-4036-9b54-a1d565dfb15f","year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:06.144188Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:bd3eb0d6e0a4b498fd47bc54f53a548b92d3b1da1312e11c62ecf0d0680ec4dd","observation_id":"6b547427-1974-4c16-a177-2ff59895bdc3","resolution":{"observed_at":"2026-08-05T10:46:13.775179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:06.214147Z","title":"Ct-glip: 3d grounded language-image pretraining with ct scans and radiology reports for full-body scenarios","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:06.214147Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:79a16a32ebd837b088a7050ec625c6c0226ddd5a1356c9e839e2cca1fbacc9c2","observation_id":"9920dd3d-25af-4526-9efc-147946bfd878","resolution":{"observed_at":"2026-08-05T10:46:06.214147Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:06.347751Z","title":"Pmc-clip: Contrastive language-image pre-training using biomedical documents","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:06.347751Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:ae1bbad12fa065f23e158a16413df80eab286e9f66d012c8360a8fb0d0dc3f09","observation_id":"045e8575-14d9-458f-90dc-c8791db2b0af","resolution":{"observed_at":"2026-08-05T10:46:06.347751Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13523","last_updated":"2025-02-25T06:19:03Z","snapshot_observed_at":"2026-07-06T19:35:17.363851Z","submitted_at":"2024-10-17T13:11:07Z","title":"Can Medical Vision-Language Pre-training Succeed with Purely Synthetic Data?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13523","snapshot_observed_at":"2026-08-05T10:46:06.490159Z","title":"Can medical vision-language pre-training succeed with purely synthetic data? arXiv preprint arXiv:2410.13523, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:06.490159Z"},"links":{"cited_paper":"/paper/2410.13523","citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:64c93a6059eff9963f8f3f0ae540aff850601fcc5ce39bf4d43cdca258ca2232","observation_id":"56045d27-ec37-4ba5-a6bd-9f2a0988974a","resolution":{"observed_at":"2026-08-05T10:46:06.490159Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:06.654963Z","title":"Improved baselines with visual instruction tuning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:06.654963Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:6f91cb40f6cb7937ea3f6816d846d5519593c892372d1f6354e98ea952f51d27","observation_id":"7cfb17f5-68a2-4784-ae44-4289145e1d0d","resolution":{"observed_at":"2026-08-05T10:46:06.654963Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1807.03748","last_updated":"2019-01-22T18:47:12Z","snapshot_observed_at":"2026-07-06T06:49:24.960992Z","submitted_at":"2018-07-10T16:52:11Z","title":"Representation Learning with Contrastive Predictive Coding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.03748","snapshot_observed_at":"2026-08-05T10:46:06.818244Z","title":"Representation learning with contrastive predictive coding","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:06.818244Z"},"links":{"cited_paper":"/paper/1807.03748","citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:778a40b282617a7c96b823c361a0b39cf31de5f486d76eb8541dd0cf58701748","observation_id":"08c8a7a7-1b04-4673-b65c-8d991d660f66","resolution":{"observed_at":"2026-08-05T10:46:06.818244Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.730957Z","title":"Unsupervised medical image translation with adversarial diffusion models","venue":null,"work_id":"123926c1-9146-48d6-b139-1d7a3cf20497","year":2023},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:06.953711Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:55abce6afacd2d5d3436891f59bed7db4c40c440171f115babd0ea531ffa4c39","observation_id":"051d5200-2466-433f-948e-fa46ba9c4c30","resolution":{"observed_at":"2026-08-05T10:46:13.736423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.716722Z","title":"On variational bounds of mutual information","venue":null,"work_id":"8834debc-f6c2-45c4-8cca-ce6e64db09ff","year":2019},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:07.058611Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:7217c1b42b8397af27272143408d680d42d8d473ed7f01d4337b8bda05863593","observation_id":"5a6d5801-2d1a-43c9-bdba-d88c5914c4df","resolution":{"observed_at":"2026-08-05T10:46:13.720929Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:07.172235Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:07.172235Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:29c2d94c97d173b4a8301f6cdfb866d7bfeeecd8aafeeef76093b20acf070ea3","observation_id":"04d8ab2e-3c09-4969-8f54-f0c86ead5096","resolution":{"observed_at":"2026-08-05T10:46:07.172235Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.691468Z","title":"Study of thoracic ct in covid-19: the stoic project","venue":null,"work_id":"cb21fb89-8126-4342-a0c3-c8256e22858f","year":2021},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:07.275215Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:2ff2a470d75c8c4c044341c2b822e08c2fe40152b5c1ff6ed4c23ddede644749","observation_id":"904762dd-f001-4ef0-96f7-33945a9c2c06","resolution":{"observed_at":"2026-08-05T10:46:13.695888Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.675692Z","title":"Deep learning in medical image analysis","venue":null,"work_id":"5d484872-8dad-4199-8db7-026d9f2ed2b2","year":2017},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:07.401048Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:7136eed76bffcf2598af609a0851d7e8cb268535084d01df87f7761c4b4e86ef","observation_id":"7526b28c-0615-4fd0-8f25-a789a2a3a0d4","resolution":{"observed_at":"2026-08-05T10:46:13.680527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.661220Z","title":"Large-scale and fine-grained vision- language pre-training for enhanced ct image understanding","venue":null,"work_id":"6610ba8f-28c9-4a11-b8a7-7119f26a0fbb","year":2025},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:07.524178Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:ab6047561ee9b7496b7c12780c82f948e672a30c3ae0423f3a3dc7f22b78a93b","observation_id":"8cea4486-36cd-46ca-a3e0-800c3835fb65","resolution":{"observed_at":"2026-08-05T10:46:13.666394Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.647076Z","title":"Bioclip: A vision foundation model for the tree of life","venue":null,"work_id":"828b54eb-3359-4986-8e2c-b4b060118710","year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:07.697454Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:4fe744e759db91feacaafaf1a3d17fcfe83650fc5317109e0bd4bd3293e63758","observation_id":"d6fa8c35-2d72-432f-8f29-319783f54832","resolution":{"observed_at":"2026-08-05T10:46:13.651773Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.07971","last_updated":"2025-05-07T14:26:09Z","snapshot_observed_at":"2026-08-04T14:30:16.365330Z","submitted_at":"2023-06-13T17:59:59Z","title":"XrayGPT: Chest Radiographs Summarization using Medical Vision-Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.07971","snapshot_observed_at":"2026-08-05T10:46:07.826433Z","title":"Xraygpt: Chest radiographs summarization using medical vision-language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:07.826433Z"},"links":{"cited_paper":"/paper/2306.07971","citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:363867edf2f7b8cb70291a5fc4eb7b75c82aa46003f868df7d583407e76d0096","observation_id":"196f8bc6-9cd3-4d50-ba35-9d041cf1c193","resolution":{"observed_at":"2026-08-05T10:46:07.826433Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.631316Z","title":"Communication errors in radiology–pitfalls and how to avoid them","venue":null,"work_id":"a180d8d2-93c9-40bd-a4bc-23fff4c39710","year":2018},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:07.970509Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:e96298abd97b85680017850453c94be49d2b7fd87c7943ecd0c0ea1e368bdcdd","observation_id":"fe0aa725-db38-4b9a-9523-c2a648ecd696","resolution":{"observed_at":"2026-08-05T10:46:13.637015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.617887Z","title":"Multi- granularity cross-modal alignment for generalized medical visual representation learning","venue":null,"work_id":"63201f56-a3b1-4e87-8ac7-429fad89e6fd","year":2022},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:08.098509Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:bc7146ac891b64669d0dedc2d526bab52fb99e20c3a970e97b3bdfc88df228b3","observation_id":"75a176bc-5a08-4d29-9b3e-e14cd42ca5df","resolution":{"observed_at":"2026-08-05T10:46:13.621985Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.603866Z","title":"Totalseg- mentator: robust segmentation of 104 anatomic structures in ct images","venue":null,"work_id":"bb0ffd0e-8f53-43e4-8830-dd8a6a994b01","year":2023},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:08.279430Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:c6207350491d3515f6459e743c775a6cb3e23ccdc4db7f6bf8e6802fb7451253","observation_id":"01ab2a9b-31b2-4afe-9136-fa8d0a2ff7f7","resolution":{"observed_at":"2026-08-05T10:46:13.608638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.586379Z","title":"Medklip: Medical knowledge enhanced language-image pre-training for x-ray diagnosis","venue":null,"work_id":"3e050f7d-e109-429f-8c43-d1a0863884fd","year":2023},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:08.403517Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:1eaa8b8e3dc9e6828e132e3b4ba1c56e3438fb2fe6ee9354f7f2531f25cd9615","observation_id":"06f050c3-69ee-4cae-a1f7-a1026382da7c","resolution":{"observed_at":"2026-08-05T10:46:13.591474Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.572570Z","title":"Unimiss: Universal medical self-supervised learning via breaking dimensionality barrier","venue":null,"work_id":"faf4c2d9-3170-4213-b52e-611c5fc6e1de","year":2022},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:08.565766Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:198f654c7f70fa65c983ca5ee41c839b6bc48e8e88dcb367c6676bfcccb4046a","observation_id":"99fd17d9-2eb1-4594-bf2f-41f070a5863a","resolution":{"observed_at":"2026-08-05T10:46:13.577184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16671","last_updated":"2025-11-23T00:34:43Z","snapshot_observed_at":"2026-08-02T18:24:11.208164Z","submitted_at":"2023-09-28T17:59:56Z","title":"Demystifying CLIP Data","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.16671","snapshot_observed_at":"2026-08-05T10:46:08.732381Z","title":"Demystifying clip data","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:08.732381Z"},"links":{"cited_paper":"/paper/2309.16671","citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:e9ec90e59c89748c3e612c44d1c868058c87fd29c9459bf917a2f25ab1e4e37e","observation_id":"eb497786-556b-4405-a3d4-fa736c636040","resolution":{"observed_at":"2026-08-05T10:46:08.732381Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.556266Z","title":"Glipv2: unifying local- ization and vl understanding","venue":null,"work_id":"554e94c8-7617-45a4-867c-00f79bbe0523","year":2022},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:08.830792Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:3f62630b3521a7ea9edf41fc22afa7ca325d4d806064137e3df6cfc39c01962f","observation_id":"57eb387b-0cc9-4b4b-947e-0e076d79af67","resolution":{"observed_at":"2026-08-05T10:46:13.561088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.542047Z","title":"Biomedgpt: A unified and generalist biomedical generative pre-trained transformer for vision, language, and multimodal tasks","venue":null,"work_id":"2a0f71f7-7700-4ccb-8ccc-4b03a75be8d3","year":2023},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:08.923378Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:125c9ed718b6a093e516ec9cf69670443080074c5859afacdc3da288b44cbf78","observation_id":"0871f1a1-4930-4509-b976-2ae4035b12ae","resolution":{"observed_at":"2026-08-05T10:46:13.546935Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.16754","last_updated":"2024-04-25T17:11:37Z","snapshot_observed_at":"2026-08-05T06:07:21.434244Z","submitted_at":"2024-04-25T17:11:37Z","title":"RadGenome-Chest CT: A Grounded Vision-Language Dataset for Chest CT Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.16754","snapshot_observed_at":"2026-08-05T10:46:09.008709Z","title":"Radgenome-chest ct: A grounded vision-language dataset for chest ct analysis","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.008709Z"},"links":{"cited_paper":"/paper/2404.16754","citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:0bd282a2bb020d8267163d3ddafa8138dd24f084d49d820738a762f396b17712","observation_id":"fd585d6f-5915-4473-b7d0-29ad8ac20d8c","resolution":{"observed_at":"2026-08-05T10:46:09.008709Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.527786Z","title":"Development of a large-scale medical visual question-answering dataset","venue":null,"work_id":"6ec14da6-fb01-41e0-b473-7e4216a47950","year":2024},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.069233Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:8894b66a95133cad654b64de822a5241a4850e1a329cc110b6d7e8746c124789","observation_id":"5278f4c0-7029-4709-814e-c6f077d70839","resolution":{"observed_at":"2026-08-05T10:46:13.532120Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.384847Z","title":"Each of these claims is supported by theoretical analysis, ablation studies, and experimental results","venue":null,"work_id":"a77d69ee-2d30-44b7-a194-dc96df160458","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.130493Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:621c776905fff7e7a693b3f3331b7f3921f2ca73ffc83c33c98ce21ad47b44db","observation_id":"52da4f73-68ac-4a46-ae3b-f2ce4f16ed22","resolution":{"observed_at":"2026-08-05T10:46:13.447833Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:13.070214Z","title":"Limitations","venue":null,"work_id":"b386c23d-a164-45d5-9c14-719f7ed8f7bb","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.166745Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:b7f2ae61de566423758c0dd9f89f41b498fe927400899aea875aa43496f03f4b","observation_id":"2e310e4c-9ace-41a2-81bd-58b7deb97277","resolution":{"observed_at":"2026-08-05T10:46:13.216943Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:12.693492Z","title":"Guidelines: • The answer NA means that the paper does not include theoretical results","venue":null,"work_id":"768d4dce-2d06-406b-9e06-543ffd83c124","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.222371Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:7c6f55fb7f9d3cf10aaec22f16d5b213476723744be9c29ae5d191a261dfcedf","observation_id":"655d84c8-671a-4e46-8840-a2ce1a9282b3","resolution":{"observed_at":"2026-08-05T10:46:12.864349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:12.407620Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"f590abe0-655b-4c16-8c6d-f79a04a91886","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.304182Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:bf86177a5d60e1c5499b5386197f3e12a772e17ec16586c6b130bb7ea1c32ab8","observation_id":"4babdb4f-17c1-4e46-af10-1ab8db572560","resolution":{"observed_at":"2026-08-05T10:46:12.564751Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:12.083058Z","title":"Guidelines: • The answer NA means that paper does not include experiments requiring code","venue":null,"work_id":"e974ff14-b685-4dc6-a0aa-f92fd016602c","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.363957Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:d558a2bb8ab2d81aef79f6af0ab37adefc84d4f9c0218525b7e7ccb038b5f639","observation_id":"42aa9b52-0cf8-4efa-b0ce-3849436a662a","resolution":{"observed_at":"2026-08-05T10:46:12.259108Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:11.938282Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"2312a503-2ada-45ba-a54e-07423e054bd0","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.437212Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:f097e3fd9a38a4b7be8cd24a09b7ed28ba851f74645fda1e65753b568a33b2eb","observation_id":"81e41ff1-e8e3-43ed-9355-b8b9868615ca","resolution":{"observed_at":"2026-08-05T10:46:12.017340Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:11.875726Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"d63cc696-aa1c-4dd1-a9ff-72d542786618","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.500264Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:076a92935778d9a894de97a4be6c4d0f49505bf845f07096a62bd71ef1b8d1e5","observation_id":"e1fad113-1c30-4f52-88ea-f48e99eed218","resolution":{"observed_at":"2026-08-05T10:46:11.928213Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:11.747564Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"38c44f8b-17df-4cb3-b5f9-50ea84dde77e","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.569808Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:673ba4d6f81919a0ea5f4dc82a310d2b0bdf70d6927d421c01cadfeeb5fc753e","observation_id":"60d98338-22c4-40ca-957a-87b29c194562","resolution":{"observed_at":"2026-08-05T10:46:11.810015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:11.637665Z","title":"All data used in this study are from publicly available, de- identified medical datasets, and no personally identifiable information (PII) was accessed or used","venue":null,"work_id":"9494fa45-26a5-4f9d-8de2-f096a03a6b13","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.648785Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:52b7b5361ebea1f87db411d4b5eb13d3650368bd5bb84684b0ec28384dbeab5b","observation_id":"fe82fdc4-fa2e-4d71-bcbe-0c308e46cdd5","resolution":{"observed_at":"2026-08-05T10:46:11.712125Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:11.481895Z","title":"Guidelines: 17 • The answer NA means that there is no societal impact of the work performed","venue":null,"work_id":"10e6da7a-d95e-49eb-ad96-0461c54fd63b","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.694965Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:93194daebc44e8561902990a34c386bcdeca3398a1425564f0e6c1f59ab91c61","observation_id":"4cbe450f-4293-472e-80de-8a150b92989b","resolution":{"observed_at":"2026-08-05T10:46:11.553592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:11.362891Z","title":null,"venue":null,"work_id":"b1f59d8c-c4b5-46c1-885c-eaab66627f1a","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.756872Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:028983d38b15eabfe7677747c8a7043acdcb9b6ad03e0ebbf68424fc59945f1e","observation_id":"91091c49-eb63-4fbe-b291-6edfceb106fd","resolution":{"observed_at":"2026-08-05T10:46:11.419872Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:11.192746Z","title":"Guidelines: • The answer NA means that the paper does not use existing assets","venue":null,"work_id":"e3232f63-ec54-41f8-b5c4-1f07944541cb","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.813237Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:0bc45d87d53b0d98879d438031562f4db6c4ddb07efab8a1675d1cedb762e429","observation_id":"68c2e891-feb6-46ed-b4b6-2720a5c2d289","resolution":{"observed_at":"2026-08-05T10:46:11.269223Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:11.052859Z","title":"These assets will be released with accompanying documentation upon paper acceptance","venue":null,"work_id":"174fb173-1c0d-4f80-9e90-30c6b5ab832b","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.853132Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:7844e9785e6ef11b04e9c85148cc7c12876e9e4e8627838770833a0c92f48cfb","observation_id":"065dba93-e8cc-466b-ba0b-2abbd75001ec","resolution":{"observed_at":"2026-08-05T10:46:11.105435Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:10.909396Z","title":"All data used are from publicly available, de-identified medical datasets with appropriate licenses and do not involve any direct interaction with individuals","venue":null,"work_id":"42424386-ceb6-4c3e-ae3d-79cfad7a5f5a","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.939998Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:bd121310701c8a449d75b2d765fd0f58eb6855f02940bbb7a49cfd24c4366c62","observation_id":"5cf22d1e-5be8-4e8f-9c0d-983ca3baaf39","resolution":{"observed_at":"2026-08-05T10:46:10.989629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:10.742870Z","title":"Therefore, IRB approval was not required","venue":null,"work_id":"0ad134fd-5474-40d8-979d-1ac3458b84dc","year":null},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.978316Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:1884952896a93832336b7094b79b7dc4c7ebf27ff0e1eeb5bb04cf5f20ceceeb","observation_id":"304aea77-f964-4354-8c2a-855d2a6a01d3","resolution":{"observed_at":"2026-08-05T10:46:10.820337Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:46:10.616630Z","title":"Answer: [Yes] Justification: Large language models such as GPT-4o and Qwen2.5, were used to rewrite radiology reports for improving semantic clarity during pretraining","venue":null,"work_id":"7a5a616c-b517-4d6f-81a9-c249099b79a0","year":2025},"citing_paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-05T10:46:09.996574Z"},"links":{"citing_paper":"/paper/2509.03800"},"observation_digest":"sha256:5f46fb93367b18d0aaf4121376cf078c9ee9a4f6ab18fbb627843a5b21a3147d","observation_id":"2905636d-5717-4d58-9d1d-4f6aeb97aac9","resolution":{"observed_at":"2026-08-05T10:46:10.677975Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2509.03800","last_updated":"2025-09-04T01:28:44Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-05T10:46:03.528441Z","submitted_at":"2025-09-04T01:28:44Z","title":"MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting"},"reference_resolution":{"displayed":60,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":20,"verified_exact":1,"verified_fuzzy":39},"total_outbound_references":60},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 2 inbound Pith citation observations for arXiv:2509.03800."}