{"as_of":"2026-08-21T06:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f1f3356d95d3e33c99e77bb816c5c34266bcd43ec31bb5d6d68cc8a2c42e45c4","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":23,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":23,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":23,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T11:37:37.921207Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-07T18:04:00.558144Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-11T13:53:57.841992Z","title":"Roentgen: vision-language foundation model for chest x-ray generation.arXiv preprint arXiv:2211.12737, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.12661","last_updated":"2025-04-23T06:29:51Z","snapshot_observed_at":"2026-08-13T03:19:50.620382Z","submitted_at":"2024-12-17T08:30:00Z","title":"MedMax: Mixed-Modal Instruction Tuning for Training Biomedical Assistants","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T13:53:57.841992Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2412.12661"},"observation_digest":"sha256:087bcfef2301f6bae63c896dd7e7af2306c7c79aca1b6b4fe30d8c5f1dc0446d","observation_id":"c7cb75f6-39f6-4346-a4fb-aa7420e799cb","resolution":{"observed_at":"2026-08-11T13:53:57.841992Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-08T12:31:21.677703Z","title":"arXiv:2211.12737","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.07516","last_updated":"2025-02-14T17:24:56Z","snapshot_observed_at":"2026-08-16T05:59:30.820706Z","submitted_at":"2025-02-11T12:36:00Z","title":"The Devil is in the Prompts: De-Identification Traces Enhance Memorization Risks in Synthetic Chest X-Ray Generation","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-08T12:31:21.677703Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2502.07516"},"observation_digest":"sha256:3c80fe223281f8194e5f8cf5f7824d02def3581904661a297c8080d79e784589","observation_id":"c409486e-88e8-4cb5-94c5-85dcfad43f6a","resolution":{"observed_at":"2026-08-08T12:31:21.677703Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-16T11:37:37.921207Z","title":"Roentgen: vision-language foundation model for chest x-ray generation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.15007","last_updated":"2025-04-24T09:52:55Z","snapshot_observed_at":"2026-08-16T11:33:26.527476Z","submitted_at":"2025-04-21T10:13:59Z","title":"Shifts in Doctors' Eye Movements Between Real and AI-Generated Medical Images","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-16T11:37:37.921207Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2504.15007"},"observation_digest":"sha256:12a15c3f6b7d75b0525a1aee3801ba89c638381b195d7b3d5fe24a94cc346351","observation_id":"7a69410c-4258-456e-86d4-9f2bba7135c7","resolution":{"observed_at":"2026-08-16T11:37:37.921207Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-15T23:09:00.865376Z","title":"Chambon, C","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.05573","last_updated":"2025-05-12T17:59:28Z","snapshot_observed_at":"2026-08-19T10:59:24.281273Z","submitted_at":"2025-05-08T18:07:16Z","title":"Prompt to Polyp: Medical Text-Conditioned Image Synthesis with Diffusion Models","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-15T23:09:00.865376Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2505.05573"},"observation_digest":"sha256:1d991d9d84436da1ceebb74f57e3557c314dafe1025a1b18b1960e709b2ac200","observation_id":"dc8bc7e2-41a2-4ca1-bd29-1b8a397959b1","resolution":{"observed_at":"2026-08-15T23:09:00.865376Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-07T14:51:38.474509Z","title":"Roentgen: visi on-language foundation model for chest x-ray generation[J]","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.22682","last_updated":"2025-05-23T03:01:22Z","snapshot_observed_at":"2026-08-17T23:09:59.498650Z","submitted_at":"2025-05-23T03:01:22Z","title":"MRI Image Generation Based on Text Prompts","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T14:51:38.474509Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2505.22682"},"observation_digest":"sha256:be33ea7de154bb5c6ad0f4bd8d5e2cee701d54bcc49739d28d6f7c148d213099","observation_id":"4f1cf7a3-8431-4593-9db1-0ab05761e7ab","resolution":{"observed_at":"2026-08-07T14:51:38.474509Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-07T12:58:36.507506Z","title":"arXiv preprint arXiv:2211.12737, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.23030","last_updated":"2025-05-29T03:16:18Z","snapshot_observed_at":"2026-08-16T06:00:19.168442Z","submitted_at":"2025-05-29T03:16:18Z","title":"Can Modern NLP Systems Reliably Annotate Chest Radiography Exams? A Pre-Purchase Evaluation and Comparative Study of Solutions from AWS, Google, Azure, John Snow Labs, and Open-Source Models on an Independent Pediatric Dataset","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T12:58:36.507506Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2505.23030"},"observation_digest":"sha256:64a7abf76c5efc452cead4b2320a29c54d9c1ab6c2ee2cedc1192d6a3d81dff3","observation_id":"e8c281b6-4154-430b-bd45-b07c6b6ee886","resolution":{"observed_at":"2026-08-07T12:58:36.507506Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-07T12:43:59.400616Z","title":"arXiv preprint arXiv:2211.12737 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.23675","last_updated":"2025-05-29T17:19:40Z","snapshot_observed_at":"2026-08-16T05:59:27.600123Z","submitted_at":"2025-05-29T17:19:40Z","title":"ImmunoDiff: A Diffusion Model for Immunotherapy Response Prediction in Lung Cancer","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T12:43:59.400616Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2505.23675"},"observation_digest":"sha256:6ccb61f4bf50757e14e3f6b6ceb7df18876fba83869991c5e08379ae3f4bf42d","observation_id":"3075a095-8025-452a-bac6-f29f6a337d17","resolution":{"observed_at":"2026-08-07T12:43:59.400616Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-06T21:23:10.395073Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.00377","last_updated":"2025-07-01T02:22:32Z","snapshot_observed_at":"2026-08-16T04:27:36.771250Z","submitted_at":"2025-07-01T02:22:32Z","title":"MedDiff-FT: Data-Efficient Diffusion Model Fine-tuning with Structural Guidance for Controllable Medical Image Synthesis","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T21:23:10.395073Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2507.00377"},"observation_digest":"sha256:de4073790e7ab57c72eaf54f124e1a5e66fbcaaaed54e13d33229baeb793a95a","observation_id":"06d97065-24a4-4a34-8b20-072f239694b0","resolution":{"observed_at":"2026-08-06T21:23:10.395073Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-06T22:02:24.884345Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.01055","last_updated":"2025-06-28T03:06:25Z","snapshot_observed_at":"2026-08-13T10:44:18.994692Z","submitted_at":"2025-06-28T03:06:25Z","title":"Prompt Mechanisms in Medical Imaging: A Comprehensive Survey","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T22:02:24.884345Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2507.01055"},"observation_digest":"sha256:8cfd0e238ca6feb757087ece8a58a440e3e9409ddca70019f11f2c92160ca507","observation_id":"a81db1bb-7c1f-48ba-a005-7c236fbfd725","resolution":{"observed_at":"2026-08-06T22:02:24.884345Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-05T22:21:02.137812Z","title":"doi:10.48550/ARXIV.2211.12737, https://arxiv.org/abs/2211.12737","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.07128","last_updated":"2025-08-10T00:32:18Z","snapshot_observed_at":"2026-08-16T05:59:31.341478Z","submitted_at":"2025-08-10T00:32:18Z","title":"Perceptual Evaluation of GANs and Diffusion Models for Generating X-rays","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-05T22:21:02.137812Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2508.07128"},"observation_digest":"sha256:470ea0268687a3ecc433399a84b065cb7730e9762374f80a39ce4f788dd56725","observation_id":"bc85a38c-e4aa-4e8c-87c1-0aa8c06a5816","resolution":{"observed_at":"2026-08-05T22:21:02.137812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-05T16:49:39.228940Z","title":"Roentgen: vision-language foundation model for chest x-ray generation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.17844","last_updated":"2025-08-25T09:49:27Z","snapshot_observed_at":"2026-08-19T11:42:10.525415Z","submitted_at":"2025-08-25T09:49:27Z","title":"Diffusion-Based Data Augmentation for Medical Image Segmentation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T16:49:39.228940Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2508.17844"},"observation_digest":"sha256:5e85d0fe65ac72807ef34edb8cd87225372460bc5959b507152688a8508e563f","observation_id":"0347d435-fb6f-40ab-9e30-1333c79ee8f1","resolution":{"observed_at":"2026-08-05T16:49:39.228940Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-04T20:20:01.713864Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.08640","last_updated":"2025-09-10T14:35:24Z","snapshot_observed_at":"2026-08-20T22:13:34.017720Z","submitted_at":"2025-09-10T14:35:24Z","title":"RoentMod: A Synthetic Chest X-Ray Modification Model to Identify and Correct Image Interpretation Model Shortcuts","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-04T20:20:01.713864Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2509.08640"},"observation_digest":"sha256:b06989926b00e79ace85c1508fd72c208b2d8b462acd87f55930b5d1377bbb4d","observation_id":"2745db78-2c01-4b21-b1c7-7a3e679ab628","resolution":{"observed_at":"2026-08-04T20:20:01.713864Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-04T19:48:41.279002Z","title":"Roentgen: Vision-language foundation model for chest x-ray generation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.09064","last_updated":"2025-09-11T00:12:59Z","snapshot_observed_at":"2026-08-16T09:03:36.071606Z","submitted_at":"2025-09-11T00:12:59Z","title":"Enhancing 3D Medical Image Understanding with Pretraining Aided by 2D Multimodal Large Language Models","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-04T19:48:41.279002Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2509.09064"},"observation_digest":"sha256:ad0710c8ca224e40973dc5f0e46555a071975b3f66cd88a2efe1f2fe56ac07cd","observation_id":"016bb8ee-56d1-48b0-9d29-d57102d10f12","resolution":{"observed_at":"2026-08-04T19:48:41.279002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-04T13:51:49.705476Z","title":"Roentgen: vision-language foundation model for chest x-ray generation.arXiv preprint arXiv:2211.12737, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.24739","last_updated":"2026-07-22T03:37:07Z","snapshot_observed_at":"2026-08-17T14:24:47.270645Z","submitted_at":"2025-09-29T13:03:57Z","title":"Toward a Vision-Language Foundation Model for Medical Data: Multimodal Dataset and Benchmarks for Vietnamese PET/CT Report Generation","version":4},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-04T13:51:49.705476Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2509.24739"},"observation_digest":"sha256:339c089d77fcf4c5aa6cd4aa331f4d1b4eff470f8b8c21ca048a12c289dc215a","observation_id":"85dd28e3-1b4b-48c2-b0cc-fa3dfba02acd","resolution":{"observed_at":"2026-08-04T13:51:49.705476Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-02T22:48:04.399284Z","title":"Langlotz, and Akshay Chaudhari","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.15811","last_updated":"2026-05-25T05:40:15Z","snapshot_observed_at":"2026-08-15T05:49:52.339085Z","submitted_at":"2026-02-17T18:47:30Z","title":"CARL-CXR: Continual Adapter-Based Routing for Task-Unknown Chest Radiograph Classification","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-02T22:48:04.399284Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2602.15811"},"observation_digest":"sha256:752cc25b20c2807ab4fcc0f9a0e4d54c3150b0e8fdc7cba861b3964f9820c2ef","observation_id":"169514f0-6ded-4adc-bd30-b443fcb39d37","resolution":{"observed_at":"2026-08-02T22:48:04.399284Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-02T18:05:36.548916Z","title":"arXiv:2211.12737 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2603.16551","last_updated":"2026-07-16T22:05:38Z","snapshot_observed_at":"2026-08-19T08:21:16.023836Z","submitted_at":"2026-03-17T14:16:42Z","title":"CompDiff: Hierarchical Compositional Diffusion for Fair and Zero-Shot Intersectional Medical Image Generation","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-02T18:05:36.548916Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2603.16551"},"observation_digest":"sha256:cd3c47519437dea288eb87a95af55afd84f72e5563e46d011ff4c20a56abcf82","observation_id":"0efe9f93-3024-4b47-a264-5216ffcda3f0","resolution":{"observed_at":"2026-08-02T18:05:36.548916Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":"2211.12737","doi":null,"metadata_source":"pith","pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-07-07T18:04:00.558144Z","title":"Roentgen: vision-language foundation model for chest x-ray generation","venue":"cs.CV","work_id":"a516c793-b325-4494-a4be-dea871e98458","year":2022},"citing_paper":{"arxiv_id":"2605.01848","last_updated":"2026-05-03T12:35:12Z","snapshot_observed_at":"2026-08-14T07:08:29.253615Z","submitted_at":"2026-05-03T12:35:12Z","title":"Disentangled Anatomy-Disease Diffusion (DADD) for Controllable Ulcerative Colitis Progression Synthesis","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-10T15:03:33.258414Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2605.01848"},"observation_digest":"sha256:d04e9dbb8a5b1c16facaca57a1ba1cedfd8e6c0761428be4253747aa130a1f77","observation_id":"6d6832b3-d773-48b1-8acd-50ace037fde1","resolution":{"observed_at":"2026-05-11T11:16:08.241890Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":"2211.12737","doi":null,"metadata_source":"pith","pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-07-07T18:04:00.558144Z","title":"Roentgen: vision-language foundation model for chest x-ray generation","venue":"cs.CV","work_id":"a516c793-b325-4494-a4be-dea871e98458","year":2022},"citing_paper":{"arxiv_id":"2605.25566","last_updated":"2026-05-25T08:18:45Z","snapshot_observed_at":"2026-08-14T06:38:10.459084Z","submitted_at":"2026-05-25T08:18:45Z","title":"Uncertainty Reasoning with Large Language Models for Explainable Disease Diagnosis","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-29T21:50:09.763331Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2605.25566"},"observation_digest":"sha256:7bfa4dcaea6110fa7bfb5e393d0de6e89f98390723ef9debe96bd466792783c5","observation_id":"554eef08-a59f-4fba-94f2-9c7806a88d2b","resolution":{"observed_at":"2026-06-29T21:53:59.267356Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":"2211.12737","doi":null,"metadata_source":"pith","pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-07-07T18:04:00.558144Z","title":"Roentgen: vision-language foundation model for chest x-ray generation","venue":"cs.CV","work_id":"a516c793-b325-4494-a4be-dea871e98458","year":2022},"citing_paper":{"arxiv_id":"2606.19460","last_updated":"2026-06-17T18:01:18Z","snapshot_observed_at":"2026-08-14T13:51:41.506054Z","submitted_at":"2026-06-17T18:01:18Z","title":"Scaling Generative Foundation Models for Chest Radiography with Rectified Flow Transformers","version":1},"reference_index":105,"source":"arxiv_source","source_observed_at":"2026-06-26T21:10:51.682435Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2606.19460"},"observation_digest":"sha256:13f9574eb5e53cffcabc7537f822b8fe34d7858807e43f69ff5f5227620b62cb","observation_id":"c4cbb580-0174-4364-aaef-05c0324a9ed9","resolution":{"observed_at":"2026-07-04T00:29:16.080925Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":"2211.12737","doi":null,"metadata_source":"pith","pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-07-07T18:04:00.558144Z","title":"Roentgen: vision-language foundation model for chest x-ray generation","venue":"cs.CV","work_id":"a516c793-b325-4494-a4be-dea871e98458","year":2022},"citing_paper":{"arxiv_id":"2607.05319","last_updated":"2026-07-06T16:58:05Z","snapshot_observed_at":"2026-08-14T06:37:17.480944Z","submitted_at":"2026-07-06T16:58:05Z","title":"Steering Optimisation Trajectories in Diffusion Representation Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-07T17:54:09.140773Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2607.05319"},"observation_digest":"sha256:a64878383591f7688ca20d73179f4f9336d78651aa783d1a2af5507809e3027e","observation_id":"4e6df1f1-baa2-470f-a1c4-a2cf41d751e0","resolution":{"observed_at":"2026-07-07T18:04:00.563306Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-02T00:34:39.329799Z","title":"arXiv preprint arXiv:2211.12737 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.14984","last_updated":"2026-07-16T13:36:48Z","snapshot_observed_at":"2026-08-18T19:56:51.731415Z","submitted_at":"2026-07-16T13:36:48Z","title":"Demographically-Conditioned Synthetic Medical Images for Bias Mitigation and Bias Detection in Disease Classifiers","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-02T00:34:39.329799Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2607.14984"},"observation_digest":"sha256:9afd62f96f9b56b6fa3ff371fdde7fc9c82cf2f6616d2bc76b9728560bc2d603","observation_id":"0da23f0c-6106-4279-8c79-01bab8aff9ad","resolution":{"observed_at":"2026-08-02T00:34:39.329799Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-01T19:54:46.306535Z","title":"Roentgen: Vision-language foundation model for chest x-ray generation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.16828","last_updated":"2026-07-18T14:03:39Z","snapshot_observed_at":"2026-08-17T19:11:58.851514Z","submitted_at":"2026-07-18T14:03:39Z","title":"UniNDM: A Unified Noise-driven Detection and Mitigation Framework Against Sexual Content in Text-to-Image Generation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T19:54:46.306535Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2607.16828"},"observation_digest":"sha256:896debe6ccc72a0e8381ea2bca03c33f4b91e8a47253d9b4914cce565120071a","observation_id":"21d2f7ff-3eb9-49d1-93df-d0df32eef50b","resolution":{"observed_at":"2026-08-01T19:54:46.306535Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12737","snapshot_observed_at":"2026-08-01T14:06:09.557339Z","title":"Roentgen: vision-language foundation model for chest x-ray generation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.18882","last_updated":"2026-07-21T09:13:07Z","snapshot_observed_at":"2026-08-17T04:41:17.776861Z","submitted_at":"2026-07-21T09:13:07Z","title":"Local Label-Informed Feature Transfer for Generating Ground-Truth Medical Images: A Comparison of GAN- and Diffusion-Based Approaches","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T14:06:09.557339Z"},"links":{"cited_paper":"/paper/2211.12737","citing_paper":"/paper/2607.18882"},"observation_digest":"sha256:1216a28ed22d15d4dd27a4485b905dad3b2470c15fbadc3d6eb9d5cddddf6f81","observation_id":"48ed98db-cd3b-4e31-8f46-92af518b1cbe","resolution":{"observed_at":"2026-08-01T14:06:09.557339Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2211.12737/citation-record","integrity":"/paper/2211.12737/integrity","json":"/paper/2211.12737/citation-record.json","paper":"/paper/2211.12737"},"outbound":[],"paper":{"arxiv_id":"2211.12737","last_updated":"2022-11-23T06:58:09Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-19T10:57:12.116518Z","submitted_at":"2022-11-23T06:58:09Z","title":"RoentGen: Vision-Language Foundation Model for Chest X-ray Generation"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:2211.12737."}