{"as_of":"2026-08-09T17:25:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:07ec05e5e1248b1728b482219e8d463d740c78943ddffe45faf6037984a9cafa","coverage":[{"denominator":21,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":21,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:36:12.724334Z","state":"measured"},{"denominator":21,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":21,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.01902/citation-record","integrity":"/paper/2506.01902/integrity","json":"/paper/2506.01902/citation-record.json","paper":"/paper/2506.01902"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:36:15.257999Z","title":"Deep learning in medical image analysis: A third eye for doctors,","venue":null,"work_id":"16b99c1b-ec28-41b4-8509-3feb408683dd","year":2019},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:10.829997Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:238a059c994ff9f53b1cdf7d63b10d2f480a22114cbffa52e3cf54dff90c3c37","observation_id":"633b41cb-0744-44e5-8de2-3f7b3138447b","resolution":{"observed_at":"2026-08-07T11:36:15.334429Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:36:10.926927Z","title":"Zero-shot learning—a comprehensive evaluation of the good, the bad and the ugly,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:10.926927Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:8a6839313139dbbfb5cf5ea5a3258e6d2e4ff833e9b5f8bd077ba64d41150219","observation_id":"9d55cf2f-cb9d-4278-9994-242b2ea03d3a","resolution":{"observed_at":"2026-08-07T11:36:10.926927Z","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":"2026-08-07T11:36:15.062784Z","title":"Learning transferable visual models from natural language super- vision,","venue":null,"work_id":"faefad16-2a65-41e5-be14-f22503b64087","year":2021},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:11.037765Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:92080ccfdd4e853b06b4782b467be40c8cbe36216a4d3d528b8185e7b7012841","observation_id":"23eae31c-6844-4a6e-b694-2791d5a5904e","resolution":{"observed_at":"2026-08-07T11:36:15.150660Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:36:14.886036Z","title":"Scaling up visual and vision-language representation learning with noisy text supervision,","venue":null,"work_id":"0ca3ff9a-7696-41dc-9ebb-32f16fbaf1c9","year":2021},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:11.147365Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:b9211fcefe8e261b27399d6ff0f8e55653c7b33f88ab45745b1d637c55ff2f6e","observation_id":"3f1463d5-58d9-4fe9-843b-83ceea490472","resolution":{"observed_at":"2026-08-07T11:36:14.990715Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:36:11.257865Z","title":"Making the Most of Text Semantics to Improve Biomedical Vision–Language Processing,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:11.257865Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:1ff51ec0ad857ff1f1cda9b06c84a32edd29408bf72cd21251f4d0272725465b","observation_id":"4adabc46-6f02-414f-81ed-c3081dcb8229","resolution":{"observed_at":"2026-08-07T11:36:11.257865Z","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":"2026-08-07T11:36:14.742361Z","title":"When and why vision-language models behave like bags-of-words, and what to do about it?","venue":null,"work_id":"9d4cac35-55fa-4466-8a11-4592453a7765","year":2022},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:11.369209Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:9c85c66c975cdd296e0094ef599163339c290a69e75f71c617d65624d251e8e1","observation_id":"ebf3608c-470c-4af6-b008-8ffeaf72f98e","resolution":{"observed_at":"2026-08-07T11:36:14.805910Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1808.06752","last_updated":"2018-08-27T16:06:44Z","snapshot_observed_at":"2026-07-06T06:56:34.657007Z","submitted_at":"2018-08-21T04:00:23Z","title":"Lessons from Natural Language Inference in the Clinical Domain","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.06752","snapshot_observed_at":"2026-08-07T11:36:11.452383Z","title":"Lessons from natural lan- guage inference in the clinical domain,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:11.452383Z"},"links":{"cited_paper":"/paper/1808.06752","citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:e1672dc772c0431aae2109ec78b609a81008689e81514e1c86fc3a3ae67c772a","observation_id":"3a2fe4b2-438d-4525-b328-e9e470a3d137","resolution":{"observed_at":"2026-08-07T11:36:11.452383Z","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":"2026-08-07T11:36:14.589926Z","title":"Improving factual completeness and con- sistency of image-to-text radiology report generation,","venue":null,"work_id":"1116a79f-d021-49a0-b0ec-c7f08f3f184d","year":null},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:11.552685Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:cba6cb814168b47e8f8671a540a669b40e8fb12c01e50ff682ce0194473bd4ab","observation_id":"3228846b-5eb7-4284-a517-7ce2fe87e845","resolution":{"observed_at":"2026-08-07T11:36:14.663254Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:36:14.399357Z","title":"Chexpert: A large chest radiograph dataset with uncertainty labels and ex- pert comparison,","venue":null,"work_id":"e1630b0e-aed4-48ba-9656-5acd958357ef","year":2019},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:11.786585Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:fd907247a71258a2198bf54e8a5b9b6aa10bf8bf5f245ac2cd748d1f26141a4a","observation_id":"b90f7903-7ad9-4b22-a44b-9bc28b5b2175","resolution":{"observed_at":"2026-08-07T11:36:14.481434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:36:14.220409Z","title":"Contrastive learning of medical visual representations from paired images and text,","venue":null,"work_id":"b19449bb-6025-4e22-9bcb-d074a8a5dbe2","year":2022},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:11.885502Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:8033a55eb40b073e1fd6cf38c7576cbbac01c207e22fa38074c29eb1f6210593","observation_id":"e64449a7-797f-4298-991b-da2c3db4d5a4","resolution":{"observed_at":"2026-08-07T11:36:14.317898Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:36:14.063665Z","title":"Joint learning of localized representations from medical im- ages and reports,","venue":null,"work_id":"6affc80b-b5ee-433c-be13-4371c7c56500","year":2022},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:11.963517Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:60abe8f065346f52837e8b244b5bf4906148698f532c5316bb3dc8df15646bec","observation_id":"4285469d-accf-4316-a9f5-f740ad6f4c00","resolution":{"observed_at":"2026-08-07T11:36:14.141935Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.10163","last_updated":"2022-10-18T21:06:29Z","snapshot_observed_at":"2026-08-07T02:27:07.862492Z","submitted_at":"2022-10-18T21:06:29Z","title":"MedCLIP: Contrastive Learning from Unpaired Medical Images and Text","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.10163","snapshot_observed_at":"2026-08-07T11:36:12.053292Z","title":"Medclip: Contrastive learning from unpaired medical images and text,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:12.053292Z"},"links":{"cited_paper":"/paper/2210.10163","citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:5e14f26ebcccb6022e012286fa67c984a9b73919e0ee765ab0760072226d21ae","observation_id":"bb87e176-0ef2-41f6-97f3-7a66dfbe47fc","resolution":{"observed_at":"2026-08-07T11:36:12.053292Z","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":"2026-08-07T11:36:13.882986Z","title":"Expert-level detection of patholo- gies from unannotated chest x-ray images via self- supervised learning,","venue":null,"work_id":"55450f99-e796-41d2-a304-d4d9a2730935","year":2022},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:12.126466Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:ebb55df2d6baf18c120ea6cdc1eacae61b0d36a00b466087ecc8ce2f0e24c289","observation_id":"e5159f0c-b5fa-4e4a-877c-c9917cdf326b","resolution":{"observed_at":"2026-08-07T11:36:13.956412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:36:13.708983Z","title":"Pubmed data download,","venue":null,"work_id":"bfd46856-5f40-4a87-a2e3-495d304537a4","year":null},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:12.171617Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:adff9a8d98f8153ed52cf8219715a2190667ed229104103bfeb4f7105c3f7139","observation_id":"90938677-ade9-4073-b59f-d009f93e7bc3","resolution":{"observed_at":"2026-08-07T11:36:13.777040Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:36:12.263639Z","title":"MIMIC-III, a freely accessible critical care database,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:12.263639Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:c54d097e88f91aa765a6f2c0b4917f01984819609ec3aeaa2d01b1938c64f5d7","observation_id":"78c2f522-1df3-440c-b82e-9f582de5a44e","resolution":{"observed_at":"2026-08-07T11:36:12.263639Z","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":"2026-08-07T11:36:13.543789Z","title":"Gloria: A multimodal global-local representation learning framework for label-efficient medical image recognition,","venue":null,"work_id":"4e2d1bbd-8b3c-4b5d-b0bc-8f9c24365b9b","year":2021},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:12.369487Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:9a4dd4496c945dcf58bbc10a7235896ae6711edcd8f504e161b5608e03c414f4","observation_id":"5dfa1b2d-c567-4320-a70f-0c99040516cd","resolution":{"observed_at":"2026-08-07T11:36:13.624497Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:36:13.285774Z","title":"Spacy 2: Natural lan- guage understanding with bloom embeddings, convolu- tional neural networks and incremental parsing. neural machine translation,","venue":null,"work_id":"7f99bde7-d30b-47cb-8ffe-536aa022badf","year":2017},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:12.437052Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:0dffc7ca244317bfe7e6c52a99cee31953691f1f66ef0b2c9205a5df7c1eac6b","observation_id":"5a6286b7-0585-4073-b95b-a4973f05ef7c","resolution":{"observed_at":"2026-08-07T11:36:13.436265Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T11:36:13.086440Z","title":"What context features can transformer language models use?","venue":null,"work_id":"2ce5d7a2-6d09-476f-8714-310a72d037bd","year":2021},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:12.561961Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:81b1ef3fb7ad97e717d95a4c718cfeb0cb0f077c737f6984c1b5d718dd8f8641","observation_id":"a2c5e2d7-7b63-4fdb-8904-ec6b09a0ca2f","resolution":{"observed_at":"2026-08-07T11:36:13.180575Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.5626/jcse.2012.6.2.168","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:36:12.843176Z","title":"Design and development of a multimodal biomedical information retrieval system,","venue":null,"work_id":"ea65258b-c468-46ac-b1fc-70db956b6d54","year":2012},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:12.656437Z"},"links":{"citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:5bdc1cc683662d7e150df9a8eadb488e8692fe1a185313b6034b67909e76f33e","observation_id":"8ed3cef4-4c0f-4adc-81be-85dacf0c6b0f","resolution":{"observed_at":"2026-08-07T11:36:12.952389Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.04747","last_updated":"2017-06-15T13:21:04Z","snapshot_observed_at":"2026-08-04T02:05:40.539691Z","submitted_at":"2016-09-15T17:32:34Z","title":"An overview of gradient descent optimization algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.04747","snapshot_observed_at":"2026-08-07T11:36:12.724334Z","title":"An overview of gradient descent optimiza- tion algorithms,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:12.724334Z"},"links":{"cited_paper":"/paper/1609.04747","citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:673fe0b25841cee3c6657406b463370d5c76e647b80cc3440fca0a419bb2bd6a","observation_id":"c26caedf-6e7e-453b-829f-8bb8686e4f5e","resolution":{"observed_at":"2026-08-07T11:36:12.724334Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.10042","last_updated":"2021-04-12T20:41:48Z","snapshot_observed_at":"2026-08-03T14:57:07.650557Z","submitted_at":"2020-10-20T05:42:47Z","title":"Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.10042","snapshot_observed_at":"2026-08-07T11:36:11.685118Z","title":null,"venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-07T11:36:11.685118Z"},"links":{"cited_paper":"/paper/2010.10042","citing_paper":"/paper/2506.01902"},"observation_digest":"sha256:e63d0c4c1075b929b764456e339f6d352045c40fe52f61bff19d57811051665b","observation_id":"fec5e85a-9246-4461-aedc-c8233b3bac18","resolution":{"observed_at":"2026-08-07T11:36:11.685118Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.01902","last_updated":"2025-06-02T17:23:25Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T10:06:54.609569Z","submitted_at":"2025-06-02T17:23:25Z","title":"Enhancing Biomedical Multi-modal Representation Learning with Multi-scale Pre-training and Perturbed Report Discrimination"},"reference_resolution":{"displayed":21,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":1,"verified_fuzzy":13},"total_outbound_references":21},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2506.01902."}