{"as_of":"2026-08-12T16:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6fb23f188b5cb092a0febf7fe7f4654ef899499883039822bd7474aea6abce75","coverage":[{"denominator":63,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":63,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:24:50.995711Z","state":"measured"},{"denominator":64,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":64,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-10T10:48:31.440624Z","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":"2026-05-10T10:49:55.984530Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"cited_work":{"arxiv_id":"2506.07984","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.07984","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Cxr-lt 2024: A miccai challenge on long-tailed, multi- label, and zero-shot disease classification from chest x-ray","venue":null,"work_id":"f20669b9-4be1-4e6a-bcdc-5434b226c61c","year":2024},"citing_paper":{"arxiv_id":"2604.15555","last_updated":"2026-04-16T22:10:09Z","snapshot_observed_at":"2026-08-11T07:24:32.927821Z","submitted_at":"2026-04-16T22:10:09Z","title":"CXR-LT 2026 Challenge: Multi-Center Long-Tailed and Zero Shot Chest X-ray Classification","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-10T10:48:31.440624Z"},"links":{"cited_paper":"/paper/2506.07984","citing_paper":"/paper/2604.15555"},"observation_digest":"sha256:a4f78695caf0ce8b7de2091f998f2d7d9b8ae1bb35a39c85afea5f46f5337c30","observation_id":"b744ac68-e63c-4a05-9049-19576d1bd039","resolution":{"observed_at":"2026-05-10T10:49:55.987610Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.07984/citation-record","integrity":"/paper/2506.07984/integrity","json":"/paper/2506.07984/citation-record.json","paper":"/paper/2506.07984"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:50.671224Z","title":"Long-tailed classification of thorax diseases on chest x-ray: A new benchmark study","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.671224Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:8b6f1cb7aa57eb7625e44caac5af01797619e873ca556c13965d3d8d57a9321d","observation_id":"3c8e7977-9141-46fe-8343-71a2eaa671ed","resolution":{"observed_at":"2026-08-07T05:24:50.671224Z","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":"2026-08-07T05:24:50.675276Z","title":"Towards long-tailed, multi-label disease classification from chest x-ray: Overview of the cxr-lt challenge.Medical Image Analysis, page 103224, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.675276Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:1b9184a044bc060f019d25e8988e5edbe8a09a0491b8c9d56ed4a1689953e4d6","observation_id":"3e952bb1-5d7f-4b00-aa5f-81349e266d5d","resolution":{"observed_at":"2026-08-07T05:24:50.675276Z","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":"2026-08-07T05:24:50.679095Z","title":"Evolution-aware V Ariance (EV A) coreset selection for medical image classification","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.679095Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:704607162f013704aec63a755b9402ddf7fbb210c5a0823ac0d2acd79c9bc468","observation_id":"c51782a9-eb14-4a4c-9c71-05acc324e8c9","resolution":{"observed_at":"2026-08-07T05:24:50.679095Z","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":"2024.10157","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:51.356901Z","title":"Denoising diffusion proba- bilistic models for addressing data limitations in chest X-ray classification.Inform","venue":null,"work_id":"2f9b543b-6b3a-4680-bdbf-4642bd907236","year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.683215Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:68d678e5b5846c42b4d9f42322cf009301aab1ebb76efbf32eb1a8ba403b2730","observation_id":"24f17d70-b2aa-4343-aa98-45ba5d9efe8b","resolution":{"observed_at":"2026-08-07T05:24:51.362703Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.820536Z","title":"Fine-grained self-supervised learning with jigsaw puzzles for medical image classification.Comput","venue":null,"work_id":"90e021f6-ee64-43fa-a684-df333b100c32","year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.686944Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:009997cdfb5cb9a9e871fadb91f07742d9230d5a1dd46fde15f5ff5d89c03b2d","observation_id":"ef4c2222-411b-4256-bd08-d001de188ba4","resolution":{"observed_at":"2026-08-07T05:24:51.824404Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.809710Z","title":"Improving generalization and personalization in long-tailed federated learning via classifier retraining","venue":null,"work_id":"4e8c884f-5198-4328-9044-4642129deb7d","year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.694632Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:0b530ccd3e9c92d4105dec8f69f7f86f7b25e1e22a3065ea07f0d5d1d896e788","observation_id":"c12f5f4f-8aad-4a9f-a108-c9fb7c368d24","resolution":{"observed_at":"2026-08-07T05:24:51.813547Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.798266Z","title":"Informatics in radiology: radiology gamuts ontology: differential diagnosis for the semantic web.Radiographics, 34(1):254–264, 2014","venue":null,"work_id":"5ee191d5-2578-444c-94fd-cbb614c4f8b0","year":2014},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.698242Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:b5d44d4b8a3cdf5bb52d4584cfe9640f491ac8dee52dab4cab874c7a0b860484","observation_id":"cb072503-7d21-4e91-9504-73621e96178e","resolution":{"observed_at":"2026-08-07T05:24:51.802356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:50.702737Z","title":"Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.702737Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:3ec4279761ca162aab93127336910bb449d4d6d2a94e11c6720d13e7aa5f64a8","observation_id":"94a5b8f7-43bd-47f7-bbae-98ec888c3306","resolution":{"observed_at":"2026-08-07T05:24:50.702737Z","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":"2026-08-07T05:24:51.780051Z","title":"Chexclusion: Fairness gaps in deep chest x-ray classifiers","venue":null,"work_id":"9b1764f4-ff2c-4414-99de-ee90720d0d60","year":2021},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.706494Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:1b5438cfa9572a951309879048dcb0a56a96d1a051bba9bf676a9201279dec2e","observation_id":"88a165d0-39b5-4539-81c4-f3b05f76ae53","resolution":{"observed_at":"2026-08-07T05:24:51.783797Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.768635Z","title":"Springer, 2018","venue":null,"work_id":"6dd4cafd-a495-423f-81e6-a79eb1c2fd78","year":2018},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.709886Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:64872c341964750952e152b71818d42149dd2479d2fc37885cb39b5902a49a72","observation_id":"cd3f22f7-c66e-43ad-9bcf-34b6e9a122ed","resolution":{"observed_at":"2026-08-07T05:24:51.772762Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.757726Z","title":"The relationship between precision-recall and roc curves","venue":null,"work_id":"d333d2f5-e19f-4bd8-9961-c23b148b733f","year":2006},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.713389Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:bbd70c803bd86ecdb36d564972dd478174ba400e9d46323ddce9b2c6ac635e27","observation_id":"5bbc630a-ddec-4527-9d22-f32303562db8","resolution":{"observed_at":"2026-08-07T05:24:51.761365Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.746351Z","title":"Long-tail zero and few-shot learning via contrastive pretrain- ing on and for small data","venue":null,"work_id":"8ed59a86-174b-4051-a59e-799b26e34025","year":2022},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.716633Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:b5bffeafa026d2d760a19a5c32a02a82d8a68c1dd61594bd582035ce1a81b216","observation_id":"6f2f5976-b8db-4414-8058-e52a437ffe2c","resolution":{"observed_at":"2026-08-07T05:24:51.750748Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.735218Z","title":"Obtaining well calibrated prob- abilities using bayesian binning","venue":null,"work_id":"ac966276-b27e-4288-81c6-f96813ccceb5","year":2015},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.720470Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:0ec03e0bf7d8eb1f6085fc95c45c3aa68f68db2c95d7ca2e59160a79f0ecb901","observation_id":"cb964558-5498-4cd4-aef0-2e9a991a8cb0","resolution":{"observed_at":"2026-08-07T05:24:51.739189Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:50.723656Z","title":"Mimic-cxr, a de-identified publicly available database of chest radiographs with free-text reports.Scientific data, 6(1):317, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.723656Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:17f324ccbda7150204cea6325c7e950de248e82bf6c79891195f6aeb1b214f2a","observation_id":"0b85c5dc-0a34-477f-8b21-8c6b2d5ba8dd","resolution":{"observed_at":"2026-08-07T05:24:50.723656Z","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":"2026-08-07T05:24:50.726954Z","title":"Padchest: A large chest x-ray image dataset with multi-label annotated reports.Medical image analysis, 66:101797, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.726954Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:fc03da1bd606f87da46b7becfb62f5187d3919a1e2bbd02e0958c5ad049cbd4d","observation_id":"5fa18d05-1815-4fbb-9eba-ea60f70c511c","resolution":{"observed_at":"2026-08-07T05:24:50.726954Z","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":"2026-08-07T05:24:51.711544Z","title":"Fleischner society: glossary of terms for thoracic imaging.Radiology, 246(3): 697–722, 2008","venue":null,"work_id":"10be59b6-0058-4e00-8d59-03576075fef3","year":2008},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.730185Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:0dd13971516d5544fc96c882922ac32aa41184139f351ad31c82580e6d1da151","observation_id":"e8a000c9-1ce6-4023-802f-69c4e0c9cf35","resolution":{"observed_at":"2026-08-07T05:24:51.715342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:50.733643Z","title":"Radiology text analysis system (radtext): Architecture and evaluation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.733643Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:933a4075a2fadbf9dd7f62b788d97e6f14cab0dab218c1e0808e94b2ac4ed1ba","observation_id":"5e3b62d9-2baf-4890-8fd2-9d1d583d82dc","resolution":{"observed_at":"2026-08-07T05:24:50.733643Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1901.07042","last_updated":"2019-11-14T17:34:51Z","snapshot_observed_at":"2026-08-02T04:11:08.699777Z","submitted_at":"2019-01-21T19:01:00Z","title":"MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.07042","snapshot_observed_at":"2026-08-07T05:24:50.737119Z","title":"Mimic-cxr-jpg, a large publicly available database of labeled chest radiographs.arXiv preprint arXiv:1901.07042, 2019","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.737119Z"},"links":{"cited_paper":"/paper/1901.07042","citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:993dbecfb3f9b0925c7f7769d94762a996b822d40d79220b0e960d79ea96d4b2","observation_id":"504d9e71-f272-4eb6-871e-57094a362beb","resolution":{"observed_at":"2026-08-07T05:24:50.737119Z","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":"2026-08-07T05:24:51.701297Z","title":"Codalab competitions: An open source platform to organize scientific challenges.Journal of Machine Learning Research, 24(198):1–6, 2023","venue":null,"work_id":"71228813-c5db-4113-a5bd-99477ffae1a5","year":2023},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.741207Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:5ed5abebc4d0ab0b385ef9d9892595add48d18a72553caaa05882273c79e6e17","observation_id":"c0818792-0369-4b0c-a606-f09e17ed613a","resolution":{"observed_at":"2026-08-07T05:24:51.704959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:50.744610Z","title":"A convnet for the 2020s","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.744610Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:87db5810c1cc29342688752707823244780b6e9f8a0df6cd4db252034d2bd74c","observation_id":"44e6e435-35ba-4fd2-86b7-bddb24fda37b","resolution":{"observed_at":"2026-08-07T05:24:50.744610Z","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":"2026-08-07T05:24:50.748576Z","title":"Efficientnetv2: Smaller models and faster training","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.748576Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:e0eceb11e6e9320831c1fbd75230643ea77b4e7fc61f8f453accb2f9600b91e2","observation_id":"e74f2092-1ad9-4135-84e6-6f29ecd356f8","resolution":{"observed_at":"2026-08-07T05:24:50.748576Z","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":"2026-08-07T05:24:51.677099Z","title":"Domain-specific language model pretraining for biomedical natural language processing, 2020","venue":null,"work_id":"bea5fce7-55ad-405c-8df7-1dc1fff9460f","year":2020},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.752251Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:5136e37719d605e2c72414a522db8177a402b8fa41e04576d1f41438054fd1fc","observation_id":"dee29f53-2f6b-40dd-9973-f8435a5cc969","resolution":{"observed_at":"2026-08-07T05:24:51.681428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.666147Z","title":"Unichest: Conquer-and-divide pre-training for multi-source chest x-ray classification.IEEE Transactions on Medical Imaging, 2024","venue":null,"work_id":"26d40f1d-e19c-4c4e-9ebc-b371be06eabb","year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.755852Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:5aa5b81454db50e211fbc705876c230c8a6abaadfd08602c8e3d80054f0e4e55","observation_id":"26109880-3fff-4d03-acd4-306fb2391bfb","resolution":{"observed_at":"2026-08-07T05:24:51.669885Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.655472Z","title":"Chexfusion: Effective fusion of multi-view features using transformers for long-tailed chest x-ray classification","venue":null,"work_id":"66e7db98-8192-4a75-aac8-bc506376578d","year":2023},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.759299Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:e26145491496980aef0188b66ebfa58af5d50b24227aed21390e0e8ce94a52cb","observation_id":"7dbbd15c-72f5-4fcc-923f-c70d0d0b1194","resolution":{"observed_at":"2026-08-07T05:24:51.659042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:50.762905Z","title":"Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.762905Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:3496c04d578e9c6f2e5ac7077f3fb97824152ca397388a6c0574e97dc386da19","observation_id":"dab87365-9ffa-4253-97c6-87f5ba71cc4d","resolution":{"observed_at":"2026-08-07T05:24:50.762905Z","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":"2026-08-07T05:24:50.766342Z","title":"Vindr-cxr: An open dataset of chest x-rays with radiologist’s annotations.Scientific Data, 9(1):429, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.766342Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:3c15ba50d1c5bf2739a86a6e7e9ae7c6cdc6cf8dcd0ccb3c2acf30642377caa0","observation_id":"e976f5cb-7eb5-4e32-b759-cb4d9196fa7c","resolution":{"observed_at":"2026-08-07T05:24:50.766342Z","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":"2026-08-07T05:24:51.632277Z","title":"Brax, brazilian labeled chest x-ray dataset.Scientific Data, 9(1):487, 2022","venue":null,"work_id":"d1159d86-f28e-40d4-83d3-7d90ffeeae7a","year":2022},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.769592Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:4b21446e2919a99afac1ccb936ab0129164bfca333f4d1e93e805137ad449c08","observation_id":"6ead3887-cda2-4147-8967-0e94bbe17bee","resolution":{"observed_at":"2026-08-07T05:24:51.635814Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.621775Z","title":"Cleft: Language-image contrastive learning with efficient large language model and prompt fine-tuning","venue":null,"work_id":"b7bb99d0-2612-469c-b40d-9115c58b7713","year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.773096Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:e9b22778946ad2472263de634ce84fc9967f5902492d50883da9f96f8afa3922","observation_id":"a8fc5658-fb5d-42c7-864a-77e1fa18b2c6","resolution":{"observed_at":"2026-08-07T05:24:51.625482Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.18119","last_updated":"2025-03-27T17:39:55Z","snapshot_observed_at":"2026-08-10T14:01:02.447584Z","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":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.18119","snapshot_observed_at":"2026-08-07T05:24:50.776412Z","title":"Multi-view and multi-scale alignment for contrastive language-image pre-training in mammography.arXiv preprint arXiv:2409.18119, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.776412Z"},"links":{"cited_paper":"/paper/2409.18119","citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:79c563a0c98c6ff7f63437594791dc091f21aafacc29a239f1a3bb25de13320c","observation_id":"4a9d9552-b4b2-409f-97b6-107c59daa605","resolution":{"observed_at":"2026-08-07T05:24:50.776412Z","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":"2026-08-07T05:24:51.609490Z","title":"Asymmetric loss for multi-label classification","venue":null,"work_id":"eb89ba11-0cf1-4c17-a062-b89b01122612","year":2021},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.780000Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:e3db29acc0ff3ba44221e08f0fad56bcffb7522611162dd01121955380f14f66","observation_id":"f1cdc2ed-02dd-4f6c-84ca-148efa53d48a","resolution":{"observed_at":"2026-08-07T05:24:51.614388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.18421","last_updated":"2024-03-27T10:18:21Z","snapshot_observed_at":"2026-08-07T07:50:55.679613Z","submitted_at":"2024-03-27T10:18:21Z","title":"BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.18421","snapshot_observed_at":"2026-08-07T05:24:50.783519Z","title":"Biomedlm: A 2.7 b parameter language model trained on biomedical text.arXiv preprint arXiv:2403.18421, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.783519Z"},"links":{"cited_paper":"/paper/2403.18421","citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:fed33d5a4adfb81d5e38321773ccbfa8c274207bbcf828e15616f5285aeb5942","observation_id":"fee3667e-5bb0-49ae-bfda-2c13a49ec6e6","resolution":{"observed_at":"2026-08-07T05:24:50.783519Z","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":"2026-08-07T05:24:51.597960Z","title":"Ml-decoder: Scalable and versatile classification head","venue":null,"work_id":"26c96615-efff-4970-865f-037ab8ce853f","year":2023},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.787492Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:0fc907168870e2f2d25783ffe79da0b4745a5c2bb653498c6e3240b9d6362d07","observation_id":"05782769-fe06-4c97-a2c8-3fc5483f5db9","resolution":{"observed_at":"2026-08-07T05:24:51.601884Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.586564Z","title":"Self-training with noisy student im- proves imagenet classification","venue":null,"work_id":"debf52f2-f9f8-47ca-a413-e72bd6040e2f","year":2020},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.790962Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:2d2b9d734f917333625612bfe24e222f84387a68a7924d1e07b8a775526b96a7","observation_id":"f74c245d-d62f-4fbb-8b14-89308b2ec665","resolution":{"observed_at":"2026-08-07T05:24:51.590844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-11T10:12:11.384939Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-07T05:24:50.794326Z","title":"Dinov2: Learning robust visual features without supervision.arXiv preprint arXiv:2304.07193, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.794326Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:ee64d24f793793b475c032357fef73bbbaaf4cef7957e976c6da6895056bfa81","observation_id":"9b37cbbf-bca0-480b-9cef-7af6208b156b","resolution":{"observed_at":"2026-08-07T05:24:50.794326Z","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":"2026-08-07T05:24:51.576034Z","title":"Transformers for image recognition at scale.Online: https://ai","venue":null,"work_id":"574e7244-24d2-4bd2-ba5e-fe0424b29a3c","year":2020},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.798589Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:f4270d3614b7003d3252f10173820dac98afa40a636445120bc99a69c474580f","observation_id":"37d9f519-54f2-41f2-93c0-f4f1f9c27b09","resolution":{"observed_at":"2026-08-07T05:24:51.579690Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.565252Z","title":"Maxvit: Multi-axis vision transformer","venue":null,"work_id":"41959e7a-8cb6-43ea-9985-669519e19b65","year":null},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.802229Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:5f10f27ecd5e8951bf16f5c205c9954eeb182b40e8bd472e15f623cb65c6011e","observation_id":"a445b4e4-9198-4940-8ad5-ca3751db0cc5","resolution":{"observed_at":"2026-08-07T05:24:51.569256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.553807Z","title":"Making the most of text semantics to improve biomedical vision–language processing","venue":null,"work_id":"84ff51a8-e52c-417f-8959-3510e668c611","year":2022},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.805955Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:00c9d83c26ffe39fea140f18402c6f367e140c02235661eff98804d4b0c361da","observation_id":"239b6213-870e-45a6-85f9-c6b2294fe757","resolution":{"observed_at":"2026-08-07T05:24:51.557858Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-07T05:24:50.810725Z","title":"Gpt-4 technical report","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.810725Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:623b26ab2ce901a05dd56a3c5ad7de40015ce2bfc0443b3fea954ecd88014778","observation_id":"43fb936e-dae4-4c9a-8a00-3b1ba3a2942a","resolution":{"observed_at":"2026-08-07T05:24:50.810725Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.02228","last_updated":"2023-04-03T09:57:51Z","snapshot_observed_at":"2026-07-06T14:37:51.682439Z","submitted_at":"2023-01-05T18:55:09Z","title":"MedKLIP: Medical Knowledge Enhanced Language-Image Pre-Training in Radiology","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.02228","snapshot_observed_at":"2026-08-07T05:24:50.814293Z","title":"Medklip: Medical knowledge enhanced language-image pre-training in radiology.arXiv preprint arXiv:2301.02228, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.814293Z"},"links":{"cited_paper":"/paper/2301.02228","citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:702667f2dca14fc90bb488224095bf9ca2116c56cfe5410ebc27a099222d9ca3","observation_id":"febfd9f0-330a-42c2-b9f3-f43d81cfbb74","resolution":{"observed_at":"2026-08-07T05:24:50.814293Z","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":"2026-08-07T05:24:50.817912Z","title":"Deep residual learning for image recog- nition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.817912Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:e9e4b05b8c7fd8ee2be6b1354bc54e5d90024ffd591f30d0b6b8abd8c1e28ff4","observation_id":"db1d42c9-1ad0-4ff6-b80c-c94f05845da2","resolution":{"observed_at":"2026-08-07T05:24:50.817912Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1904.03323","last_updated":"2019-06-20T20:41:58Z","snapshot_observed_at":"2026-08-11T08:24:54.476567Z","submitted_at":"2019-04-06T00:34:39Z","title":"Publicly Available Clinical BERT Embeddings","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.03323","snapshot_observed_at":"2026-08-07T05:24:50.821228Z","title":"Publicly available clinical bert embeddings.arXiv preprint arXiv:1904.03323, 2019","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.821228Z"},"links":{"cited_paper":"/paper/1904.03323","citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:096320a18a4bd14d44bf7aa8f8b2fc14fb5f1fdda91f8b45a7f757995a8f19b5","observation_id":"107e9779-4578-49c1-a07f-97774d2dc874","resolution":{"observed_at":"2026-08-07T05:24:50.821228Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.01948","last_updated":"2024-07-02T04:39:19Z","snapshot_observed_at":"2026-08-12T01:14:12.050240Z","submitted_at":"2024-07-02T04:39:19Z","title":"Extracting and Encoding: Leveraging Large Language Models and Medical Knowledge to Enhance Radiological Text Representation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.01948","snapshot_observed_at":"2026-08-07T05:24:50.824811Z","title":"Extracting and encoding: Leveraging large language models and medical knowledge to enhance radiological text representation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.824811Z"},"links":{"cited_paper":"/paper/2407.01948","citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:4ed33f807705a477a1d9e7c1eddb6b697661fb8e55b2e0e814b05bf9a630e861","observation_id":"7a4825d3-1e66-40d3-a024-93d598a9168b","resolution":{"observed_at":"2026-08-07T05:24:50.824811Z","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":"2026-08-07T05:24:51.536678Z","title":"Densely connected convolutional networks","venue":null,"work_id":"28811476-0dca-4fb1-8428-0a179783e778","year":2017},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.828947Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:1ed9283384c4eceb6e6c0433aeee8b73460749f44a3559d021ee21f088960ddc","observation_id":"77021129-3a45-4a50-94fe-56942aa0a893","resolution":{"observed_at":"2026-08-07T05:24:51.540358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:50.832445Z","title":"Sigmoid loss for language image pre-training","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.832445Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:347ee71c9015373a3de551a931dc7ff0fffdddfdd9527cff15e7ed22a197218e","observation_id":"dd23bc15-eab6-4b02-a18e-6fe4b09a869d","resolution":{"observed_at":"2026-08-07T05:24:50.832445Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.04676","last_updated":"2022-02-08T16:36:12Z","snapshot_observed_at":"2026-08-12T10:25:21.860679Z","submitted_at":"2022-01-12T20:02:32Z","title":"UniFormer: Unified Transformer for Efficient Spatiotemporal Representation Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.04676","snapshot_observed_at":"2026-08-07T05:24:50.836086Z","title":"Uni- former: Unified transformer for efficient spatiotemporal representation learning.arXiv preprint arXiv:2201.04676, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.836086Z"},"links":{"cited_paper":"/paper/2201.04676","citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:13233e441e9de9f15a753c76afb723a5388e1a77c7523284907fe94f50eaf62b","observation_id":"e7a92280-f4e6-4c0e-9459-6e598d0b480a","resolution":{"observed_at":"2026-08-07T05:24:50.836086Z","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":"2026-08-07T05:24:51.519859Z","title":"Film: Visual reasoning with a general conditioning layer","venue":null,"work_id":"069926de-dd2a-4606-9908-b1e05a4d8fd7","year":2018},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.840270Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:8c8d140e30ed0d35fe90a44da2969dfe25fc21495916b64393f38bc1a1247ec8","observation_id":"50bac590-f508-4a54-8ede-e5c904c67059","resolution":{"observed_at":"2026-08-07T05:24:51.523513Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.16563","last_updated":"2024-09-25T02:29:44Z","snapshot_observed_at":"2026-08-09T17:47:31.453915Z","submitted_at":"2024-09-25T02:29:44Z","title":"Enhancing disease detection in radiology reports through fine-tuning lightweight LLM on weak labels","version":1},"cited_work":{"arxiv_id":"2409.16563","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.16563","snapshot_observed_at":"2026-08-07T05:24:51.042849Z","title":"Enhancing disease detection in radiology reports through fine-tuning lightweight LLM on weak labels","venue":"cs.AI","work_id":"17221042-dc1d-467d-ba34-5302d3f3e0db","year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.843763Z"},"links":{"cited_paper":"/paper/2409.16563","citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:9177c514e89afd239c911c66a9f13f60259e7b520784fba5b952cb0fdfce4d10","observation_id":"1785aca6-faa8-4038-b2bd-f4fa63584187","resolution":{"observed_at":"2026-08-07T05:24:51.049644Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:50.847803Z","title":"Transformers in vision: A survey.ACM computing surveys (CSUR), 54(10s):1–41, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.847803Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:fb1d7a3d46f8251c971fadd1bb183712b18d718aa0eac2d5dee0bcab9769fec1","observation_id":"4a1a32ac-291f-4576-a3a6-f2926d3c04e9","resolution":{"observed_at":"2026-08-07T05:24:50.847803Z","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":"2026-08-07T05:24:51.501676Z","title":"Hybrid cnn-vit models for medical image classification","venue":null,"work_id":"5f7617b4-2e74-4604-83d1-a393836d80ad","year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.851412Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:060c95093f984b4c8bd132eb7ce953ac3252c1764a8ee5b09f8102a7d997272f","observation_id":"d86ec6f5-85e2-41ef-82a7-e65224e5000d","resolution":{"observed_at":"2026-08-07T05:24:51.505842Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.489563Z","title":"Ensemble deep learning: A review.Engineering Applications of Artificial Intelligence, 115:105151, 2022","venue":null,"work_id":"993f1f67-8969-4044-8ac6-1771228c9b90","year":2022},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.854937Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:6a00f72155d19b105ca7b2a42a30cf10e47c44581d1aaae5c07c894b3bbe30ed","observation_id":"48ccb4c0-bdc6-40a5-aa2b-60bd04c31141","resolution":{"observed_at":"2026-08-07T05:24:51.494033Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-02T23:41:42.474354Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-07T05:24:50.952221Z","title":"Deep ensembles: A loss landscape perspec- tive.arXiv preprint arXiv:1912.02757, 2019","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.952221Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:465ed13dc29a5ec37c74b586b75c1ee6230163c94abe4f211f4e496b8fee93f2","observation_id":"fde0c10e-f5de-4a42-8961-229a547211bb","resolution":{"observed_at":"2026-08-07T05:24:50.952221Z","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":"2026-08-07T05:24:51.478170Z","title":"A comprehensive survey of image augmentation techniques for deep learning.Pattern Recognition, 137:109347, 2023","venue":null,"work_id":"408d47e5-3148-400b-ab98-613c761f5f23","year":2023},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.956479Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:a9a2bf0802713a3f678775bc291a6b3beb12459b725eb8a6c40ff2c808afbf56","observation_id":"3d61949a-4ffb-464c-a28e-2082c0a3c3a4","resolution":{"observed_at":"2026-08-07T05:24:51.481993Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.467320Z","title":"Deep hierarchical multi-label classification of chest x-ray images","venue":null,"work_id":"dbba0cf4-25c6-482c-9209-423c0fefc089","year":2019},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.960700Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:5b24f7f4b907308ee83087e19cc0d3b08325fed386a122931b27d9c5e821a099","observation_id":"871845cd-72e3-4fe1-a6e8-e81b4fa9fd84","resolution":{"observed_at":"2026-08-07T05:24:51.471226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.456503Z","title":"Clinical-bert: Vision-language pre-training for radiograph diagnosis and reports generation","venue":null,"work_id":"12639be3-58f7-4d1d-936c-33c7549b5ba8","year":2022},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.965003Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:5e3a747539bc21c9572d689dfc00d7209ad38eaacd05597be380bffae073267b","observation_id":"be08904e-c9b7-46e5-bca0-8dd7eecc69f8","resolution":{"observed_at":"2026-08-07T05:24:51.460152Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.445977Z","title":"Vilmedic: a framework for research at the intersection of vision and language in medical ai","venue":null,"work_id":"5d5314bb-6a99-45ac-b4c1-5e2309edff78","year":2022},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.969315Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:0f8d2a90c2c2b3d7676c4b99ec60bcfad01f522384250047ff1f06fd8fa81f55","observation_id":"7d9339ee-84c7-41cb-b8f0-78c438d5b8ba","resolution":{"observed_at":"2026-08-07T05:24:51.449520Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.435030Z","title":"Multi-modal understanding and generation for medical images and text via vision-language pre-training.IEEE Journal of Biomedical and Health Informatics, 26(12):6070–6080, 2022","venue":null,"work_id":"72ea8218-1133-42b3-9791-44cff17258aa","year":2022},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.972885Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:b8adff7b335b382db18bf3bcf331dbac04caae2f5de6a8301b1ac646de2dd273","observation_id":"f1f8419d-e3d1-4375-8e31-64ee417eaade","resolution":{"observed_at":"2026-08-07T05:24:51.439253Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:50.976571Z","title":"Llava-med: Training a large language-and-vision assistant for biomedicine in one day.Advances in Neural Information Processing Systems, 36, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.976571Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:880c35a44d9590591644f15eecf669e815f62948a1a273399109f81cfa918fac","observation_id":"23de70fd-ee3a-45ea-9855-d1ff64cb34e8","resolution":{"observed_at":"2026-08-07T05:24:50.976571Z","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":"2026-08-07T05:24:50.981011Z","title":"Med-flamingo: a multimodal medical few-shot learner","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.981011Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:1aa78cac63f26595ce0192c970d08800d4db790ce1f7f80920bbdb2647899cf3","observation_id":"cb59e8c4-52c9-40d1-a510-eba766b1fe69","resolution":{"observed_at":"2026-08-07T05:24:50.981011Z","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":"2026-08-07T05:24:51.407011Z","title":"Improving model fairness in image-based computer-aided diagnosis.Nature Communications, 14(1):6261, 2023","venue":null,"work_id":"2981c93a-980c-4022-9bc4-2ddb78867169","year":2023},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.984881Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:6bce29ae1eae12f700040b101acc8954aef7e1dc0cf87c06976a6f8fe01934c4","observation_id":"dd1c6cd0-1d24-4d10-b60b-f75e53b0e13e","resolution":{"observed_at":"2026-08-07T05:24:51.411986Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.394752Z","title":"Hurdles to artificial intelligence deployment: Noise in schemas and “gold” labels.Radiology: Artificial Intelligence, 5(2):e220056, 2023","venue":null,"work_id":"4195d3e9-01ac-48ec-a3cd-f45da2ff4351","year":2023},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.988487Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:5f02cf4c69265d493691064744f156c85cc170483ca7612d4fb06d521ae18863","observation_id":"219b2ec9-0944-4b90-b7d5-84ee32378968","resolution":{"observed_at":"2026-08-07T05:24:51.398907Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.382543Z","title":"Large-scale long-tailed disease diagnosis on radiology images.Nature Communications, 15(1):10147, 2024","venue":null,"work_id":"827753fb-02c2-4612-a982-baea1604c2d7","year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.992193Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:050bb99da3a1b7fc6ed27f2cf7deba6307af2e7e2d4bd7bf9026cbdd2625eb7d","observation_id":"328be7b0-9c5c-4425-aaf7-520ace0d0ce0","resolution":{"observed_at":"2026-08-07T05:24:51.386417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:51.370385Z","title":null,"venue":null,"work_id":"d4a2719b-d4df-418d-8a02-035441610639","year":2021},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.995711Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:53bbd5b5932aaa016bfa9768ce386457d49120cd8a819f6a66a35c15ad57c979","observation_id":"8ef1864f-7d93-4c5b-82e1-df768e6dbe6e","resolution":{"observed_at":"2026-08-07T05:24:51.374165Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T05:24:50.690807Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":4825,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.690807Z"},"links":{"citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:3db350f56901c8e43b30ec839b615b3d821386016377f948bfda97f57a02a9a2","observation_id":"fab4b524-f516-468e-8af0-de899525f692","resolution":{"observed_at":"2026-08-07T05:24:50.690807Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray"},"reference_resolution":{"displayed":63,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":28,"verified_exact":1,"verified_fuzzy":33},"total_outbound_references":63},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 1 inbound Pith citation observation for arXiv:2506.07984."}