{"as_of":"2026-08-08T06:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c0649f1880e443793cc56a450e68ab69fc1d7bf2fb58d147ddbd4d85e2d7ef0c","coverage":[{"denominator":48,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":48,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:23:34.251478Z","state":"measured"},{"denominator":48,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":48,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2506.14451/citation-record","integrity":"/paper/2506.14451/integrity","json":"/paper/2506.14451/citation-record.json","paper":"/paper/2506.14451"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:23:40.877781Z","title":"Ai agriculture: Boost yields with yolo11","venue":null,"work_id":"6b2c7a5e-d209-474f-b40c-5714b6c3008f","year":2024},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:27.265747Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:9dc4af31852f02e6048cfe09e9299bcbd332ea09252f695eeb4947d0bdcde5dd","observation_id":"ec56a057-e04d-4262-8001-903c35a4029f","resolution":{"observed_at":"2026-08-07T00:23:40.967727Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:23:40.536950Z","title":"Video alarms for 24/7 security & monitoring","venue":null,"work_id":"e9a12633-5ce0-48f6-9475-5ce8fc87d08d","year":2025},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:27.418380Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:17854e9086dcef220f51052ec1b21fc2156ba6118c01af529714315e156568c6","observation_id":"c7f06b3d-0d6d-4bca-9e00-731828a23a25","resolution":{"observed_at":"2026-08-07T00:23:40.739764Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:23:40.283975Z","title":"Babydoctor","venue":null,"work_id":"9e138f08-07d4-44e8-9f0e-72df294863e3","year":2023},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:27.656722Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:41464b6b70079d126e777963f23b30604d949a3bcf171d0a2339fb888d07be37","observation_id":"bfa3fdd1-49fd-4511-926c-a17d98f64c3e","resolution":{"observed_at":"2026-08-07T00:23:40.414749Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.05977","last_updated":"2023-07-21T22:33:49Z","snapshot_observed_at":"2026-07-06T15:01:18.299343Z","submitted_at":"2023-03-10T15:17:22Z","title":"Open-Ended Medical Visual Question Answering Through Prefix Tuning of Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.05977","snapshot_observed_at":"2026-08-07T00:23:27.807414Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:27.807414Z"},"links":{"cited_paper":"/paper/2303.05977","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:fc69d834e3d14c60b37e059a9bac3723c964b3f77be19a59831ecd81fc3fccbe","observation_id":"7f9771bc-cce5-4c08-b089-e7182919ab72","resolution":{"observed_at":"2026-08-07T00:23:27.807414Z","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":"2026-08-07T00:23:27.948216Z","title":"Large language models encode clinical knowledge","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:27.948216Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:0e51fdcf85f7cae898a725532c144c57b8f9affc489906e25a1568736290c9ea","observation_id":"4539574b-bd30-4d18-b4d9-921ead02e053","resolution":{"observed_at":"2026-08-07T00:23:27.948216Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.00890","last_updated":"2023-06-01T16:50:07Z","snapshot_observed_at":"2026-07-29T15:30:39.490502Z","submitted_at":"2023-06-01T16:50:07Z","title":"LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.00890","snapshot_observed_at":"2026-08-07T00:23:28.089245Z","title":"Llava-med: Training a large language-and-vision assistant for biomedicine in one day, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:28.089245Z"},"links":{"cited_paper":"/paper/2306.00890","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:2ff6bab7e934a05f6bac13bc192e50572904e2d33bde666b17dec63d0097afa2","observation_id":"f54cbccb-7601-4b8d-8582-8583470fb906","resolution":{"observed_at":"2026-08-07T00:23:28.089245Z","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":"2026-08-07T00:23:28.220965Z","title":"All you may need for VQA are image captions","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:28.220965Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:5957c353f9862d88526bfa716783cb6075efb39159b94d7b7e918e8fe194ef32","observation_id":"fe28cd94-c7d3-457b-922f-f142786229b3","resolution":{"observed_at":"2026-08-07T00:23:28.220965Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.04372","last_updated":"2022-09-09T16:11:11Z","snapshot_observed_at":"2026-08-06T22:59:36.269223Z","submitted_at":"2022-09-09T16:11:11Z","title":"Pre-training image-language transformers for open-vocabulary tasks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.04372","snapshot_observed_at":"2026-08-07T00:23:28.371503Z","title":"Pre-training image-language transform- ers for open-vocabulary tasks, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:28.371503Z"},"links":{"cited_paper":"/paper/2209.04372","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:3a647216471735bf4a7989eab984913b96be36cc044523e3bcd4d7257a9218c9","observation_id":"d1162de9-890e-4f20-a76d-1880e20ce34c","resolution":{"observed_at":"2026-08-07T00:23:28.371503Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.07726","last_updated":"2024-10-10T17:28:23Z","snapshot_observed_at":"2026-08-05T10:06:10.880743Z","submitted_at":"2024-07-10T14:57:46Z","title":"PaliGemma: A versatile 3B VLM for transfer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.07726","snapshot_observed_at":"2026-08-07T00:23:28.513170Z","title":"PaliGemma: A versatile 3B VLM for transfer","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:28.513170Z"},"links":{"cited_paper":"/paper/2407.07726","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:6488b7cf0c35b2aded5a6edb0fd229774dccbc223c3d2a796e7b38fe540f99c9","observation_id":"4000eada-f398-4613-9ea6-deae126fac19","resolution":{"observed_at":"2026-08-07T00:23:28.513170Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-07T07:43:16.294957Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-07T00:23:28.620385Z","title":"Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:28.620385Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:43175501b0d86721f75e48477241975eb3d66f67989ebf526727b6af9e5c78b5","observation_id":"a9fa2a7e-21b0-410a-b5aa-2ee7e433f06f","resolution":{"observed_at":"2026-08-07T00:23:28.620385Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-07T00:23:28.726343Z","title":"Slake: A semantically- labeled knowledge-enhanced dataset for medical visual question answering, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:28.726343Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:6ae01ac04e389023147f9e14f57e45e20021c18f0c9fb55c4854b51f701e0dfc","observation_id":"30253ec1-9cae-49de-a3d9-70dd616e2b02","resolution":{"observed_at":"2026-08-07T00:23:28.726343Z","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":"2026-08-07T00:23:40.041841Z","title":"Pmc-vqa dataset, 2023","venue":null,"work_id":"cd3cadd4-c30e-42ee-87ce-a20dc8222803","year":2023},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:28.888678Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:d71c8498dd724e2840d86db232cdb67b17bfdb02ddfce855d4db8a771bb43fab","observation_id":"1bcf2d61-6aa5-4f61-b3bd-31817e2745d0","resolution":{"observed_at":"2026-08-07T00:23:40.164049Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:23:39.841520Z","title":"Friedrich","venue":null,"work_id":"0d9eb60c-720d-4aee-8cac-d837893cdd73","year":2018},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:29.062397Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:448d8f668087304be278c750ce895920790b055828e16bfeced768e2a13407c6","observation_id":"3e7782c8-cf99-42e5-8da6-7863d4c2895d","resolution":{"observed_at":"2026-08-07T00:23:39.927335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:23:39.633117Z","title":"Medpix 2.0: A comprehensive multimodal biomedical dataset for advanced ai applications,","venue":null,"work_id":"e9cfe1bd-b4c3-4e26-94a3-c5ea7b22287e","year":null},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:29.278258Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:016c2e11827e0aa69baf92df4678a931b8b8c2b3dfff5b85ffa198e563814b7b","observation_id":"5b8dd4e6-d4df-453e-92b9-fb8b6674edfd","resolution":{"observed_at":"2026-08-07T00:23:39.719471Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.10415","last_updated":"2024-09-08T01:04:35Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-05-17T17:50:16Z","title":"PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.10415","snapshot_observed_at":"2026-08-07T00:23:29.522542Z","title":"Pmc-vqa: Visual instruction tuning for medical visual question answering, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:29.522542Z"},"links":{"cited_paper":"/paper/2305.10415","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:b399c865e244456edeaad6437f7ac3ce6faa3db08a13a4c40eae74416e72069a","observation_id":"e4d07c8a-2724-44c8-9b77-9cbe7892e121","resolution":{"observed_at":"2026-08-07T00:23:29.522542Z","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":"2026-08-07T00:23:39.417444Z","title":"ChatGPT: A Large Language Model","venue":null,"work_id":"a11ac7b0-860a-4749-a754-af7f408a55d2","year":2024},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:29.686173Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:7f2429f5359c3789cb9841ab99cdbd31a9f621bb222789f27bed5da0feb9b1fd","observation_id":"a09c52bf-c3ae-4769-837f-400ce84440a6","resolution":{"observed_at":"2026-08-07T00:23:39.521645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:23:39.165993Z","title":"Healthsearchqa","venue":null,"work_id":"1dce7105-2417-4e8c-8aef-fa19ab1cbd30","year":2023},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:29.811893Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:51cb00dfc45759e79415066c10199568dbdd1182133811695b9a28cb335f3e70","observation_id":"cc9fb1ab-c5b9-41ee-b940-03cbe2c3cd8a","resolution":{"observed_at":"2026-08-07T00:23:39.299179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.11416","last_updated":"2022-12-06T21:39:48Z","snapshot_observed_at":"2026-07-06T14:08:18.855958Z","submitted_at":"2022-10-20T16:58:32Z","title":"Scaling Instruction-Finetuned Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.11416","snapshot_observed_at":"2026-08-07T00:23:29.950617Z","title":"Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:29.950617Z"},"links":{"cited_paper":"/paper/2210.11416","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:1563e71771f515899c12f1a75ab17a68515c1f7780ae2020a789de7309fa8d66","observation_id":"57de0cb8-6f11-42f4-9d75-99494a06c8e8","resolution":{"observed_at":"2026-08-07T00:23:29.950617Z","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":"2026-08-07T00:23:38.833621Z","title":"PubMed Central (PMC), 2024","venue":null,"work_id":"bdfc7dfb-5469-4ccd-9ff6-6a426625d64e","year":2024},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:30.128714Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:09a51c4d511d83563400e750bd601e360e5011579a5ad885f0c09e71d8ee24d3","observation_id":"b8c58e19-c26b-4cbf-bcfe-f0b155d32171","resolution":{"observed_at":"2026-08-07T00:23:38.989774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:23:38.485108Z","title":"Nvidia a100 tensor core gpu, 2020","venue":null,"work_id":"17688cef-cdb8-4132-a4fa-743d497486bb","year":2020},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:30.319813Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:da672eb53cf8fcf23dd7282171854f517b621aab3758662781fa8c52bd98ad72","observation_id":"4fa5e36c-643f-4338-92e0-8ee30e3622c7","resolution":{"observed_at":"2026-08-07T00:23:38.646705Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-07T00:23:30.450629Z","title":"Llama: Open and efficient foundation language models, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:30.450629Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:88a30d63c3d31666bb7740742a885df6fb92f7293c0657cdb693912e045131ac","observation_id":"831b2eae-40e2-4858-ba9b-ecc6360b60ed","resolution":{"observed_at":"2026-08-07T00:23:30.450629Z","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":"2026-08-07T00:23:38.180986Z","title":"Hewett, Jamie Huynh, Mojan Javaheripi, Xin Jin, Piero Kauffmann, Nikos Karampatziakis, Dongwoo Kim, Mahmoud Khademi, Lev Kurilenko, James R","venue":null,"work_id":"e1d76cfd-8e0f-4030-858e-729459ea9b50","year":2024},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:30.594413Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:368c8cc844a7513fca75e39f7e7bb5c1f9d7a5bd2874e5f57d866ba84484cf1e","observation_id":"3ac30739-9eba-4feb-9db3-532bf6a81145","resolution":{"observed_at":"2026-08-07T00:23:38.318674Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:23:37.794078Z","title":"Show and tell: A neural image caption generator","venue":null,"work_id":"3288aaa1-f8ff-4cc4-a2b9-5a46e53dd0c3","year":2015},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:30.705884Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:620b46e71624102da51116df0343494d8c414e54b72c9645d18eb040c68b9185","observation_id":"8e293975-e68e-47a1-be04-f74b75299807","resolution":{"observed_at":"2026-08-07T00:23:37.961957Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:23:37.556186Z","title":"Referitgame: Referring to objects in photographs of natural scenes","venue":null,"work_id":"3a4015d0-2232-4fed-b569-6a1f037a8a66","year":2014},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:30.744779Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:b4d1740120b81a7cd50868d2ca19f94dc0a3f59ae066ffe7c93ec938f6eca353","observation_id":"5b7c4b12-36c4-4440-aa26-94f877dc2130","resolution":{"observed_at":"2026-08-07T00:23:37.666127Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:23:30.809954Z","title":"Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:30.809954Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:39cd8daec450daf75a16c8abd6bc8d9d7e7d90bc7fefee944e9dbacb0a781edf","observation_id":"c0720076-7434-4d3b-9187-7ab8b2d5bc05","resolution":{"observed_at":"2026-08-07T00:23:30.809954Z","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":"2026-08-07T00:23:30.876388Z","title":"Wit: Wikipedia-based image text dataset for multimodal multilingual machine learning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:30.876388Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:5e649260c5fc3a587eeef530f1da25f97e8e7e48c3fb03104f93ee84be42a76d","observation_id":"bbbce065-2314-4c16-9136-1ed86bdef1c8","resolution":{"observed_at":"2026-08-07T00:23:30.876388Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.15343","last_updated":"2023-09-27T12:05:41Z","snapshot_observed_at":"2026-07-06T15:08:30.190912Z","submitted_at":"2023-03-27T15:53:01Z","title":"Sigmoid Loss for Language Image Pre-Training","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.15343","snapshot_observed_at":"2026-08-07T00:23:30.994202Z","title":"Sigmoid loss for language image pre-training, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:30.994202Z"},"links":{"cited_paper":"/paper/2303.15343","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:fc3be00112e597e6e7935d9f17e3fcecf8e307d2c138cae0c77ca14b87dffe7f","observation_id":"e1978bb5-3fc9-45e6-af55-31c7f0705918","resolution":{"observed_at":"2026-08-07T00:23:30.994202Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1808.06226","last_updated":"2018-08-19T16:49:06Z","snapshot_observed_at":"2026-07-06T06:56:20.935388Z","submitted_at":"2018-08-19T16:49:06Z","title":"SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.06226","snapshot_observed_at":"2026-08-07T00:23:31.138731Z","title":"Sentencepiece: A simple and language independent subword tokenizer and detokenizer for neural text processing, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:31.138731Z"},"links":{"cited_paper":"/paper/1808.06226","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:dc049bc9c885fc2acd7a4a986ea4ea20b05e073f5d60a83db773f780ef0ea49a","observation_id":"33b1f385-4617-4822-b532-f7b89672dace","resolution":{"observed_at":"2026-08-07T00:23:31.138731Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00118","last_updated":"2024-10-02T15:22:49Z","snapshot_observed_at":"2026-08-02T16:20:09.773989Z","submitted_at":"2024-07-31T19:13:07Z","title":"Gemma 2: Improving Open Language Models at a Practical Size","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00118","snapshot_observed_at":"2026-08-07T00:23:31.335216Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:31.335216Z"},"links":{"cited_paper":"/paper/2408.00118","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:0c2a2064fe7b84156e25be4ba4b489647aab2ebaf98955d33181b9e93fc0b564","observation_id":"e61a3d70-704c-4738-a674-5cf794f2ea23","resolution":{"observed_at":"2026-08-07T00:23:31.335216Z","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":"2026-08-07T00:23:31.482403Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:31.482403Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:28c7b6ee2a1aba18afa1cb8cb639c2247eb49ede76f49c10b6a3b0ce544bbb79","observation_id":"289501d2-eec9-4c8c-9733-645b9a3e14fb","resolution":{"observed_at":"2026-08-07T00:23:31.482403Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03118","last_updated":"2024-06-24T22:45:20Z","snapshot_observed_at":"2026-07-06T17:55:24.972926Z","submitted_at":"2024-04-03T23:57:34Z","title":"LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03118","snapshot_observed_at":"2026-08-07T00:23:31.623245Z","title":"Lvlm-interpret: An interpretability tool for large vision-language models, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:31.623245Z"},"links":{"cited_paper":"/paper/2404.03118","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:d921dda1576eeb306341023c29cbfa6e5af296e8d1704a232bfcaedd7bf99d93","observation_id":"5e4f2de0-b97d-40f0-980b-4e688a2f2045","resolution":{"observed_at":"2026-08-07T00:23:31.623245Z","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":"2026-08-07T00:23:37.125682Z","title":"Searching for unintended biases with saliency","venue":null,"work_id":"46db2bfe-d84f-474c-96a8-f89a081093d4","year":2022},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:31.772560Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:c08a80af535c54266c3e8108a917b40b7f097438fecb2e8b3128fa579de2573b","observation_id":"93204a6e-e295-487d-a9b2-c0c4d5cdc31d","resolution":{"observed_at":"2026-08-07T00:23:37.379690Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1706.03762","last_updated":"2023-08-02T00:41:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-06-12T17:57:34Z","title":"Attention Is All You Need","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.03762","snapshot_observed_at":"2026-08-07T00:23:31.949289Z","title":"Gomez, Lukasz Kaiser, and Illia Polosukhin","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:31.949289Z"},"links":{"cited_paper":"/paper/1706.03762","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:36f9a582365cc8fc053999f898b7e70d525933ceb0d14f1d01816077efaff2e1","observation_id":"ae0d4fd1-efac-4eaf-9544-ae9fb747d88d","resolution":{"observed_at":"2026-08-07T00:23:31.949289Z","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":"2026-08-07T00:23:32.128508Z","title":"Transformer interpretability beyond attention visualization","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:32.128508Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:783a5a5b90055d84d55995c82a7b352005ac0122ed46a9a555b0e618be839280","observation_id":"f63b4285-b633-469b-ad53-2207b4205ba5","resolution":{"observed_at":"2026-08-07T00:23:32.128508Z","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":"2026-08-07T00:23:36.711253Z","title":"Explainability for vision transformers","venue":null,"work_id":"7f6f5c23-93a8-46f2-8ca1-6a473a9ed828","year":2021},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:32.290834Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:666a2f41d2f31e4bab68cf19be5f1edec86d6ebfa71ffa089af4bb396776a517","observation_id":"59422169-b181-46bf-9803-d3861e16fe34","resolution":{"observed_at":"2026-08-07T00:23:36.907413Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:23:36.450821Z","title":"MedPix: Free Online Medical Image Database","venue":null,"work_id":"5ee89f25-49a7-4d79-85ad-5d7f968a413b","year":2024},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:32.496897Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:464649cd3fd3304e475aa2cf618e60fa1a32202713c3288a5bb12756d50d1f26","observation_id":"655eca3d-cd21-4dd0-8210-4857c8648b83","resolution":{"observed_at":"2026-08-07T00:23:36.596688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:23:36.125041Z","title":"Lin et al","venue":null,"work_id":"f9a83b51-e36f-4c83-8a4b-dadb79bcee2d","year":2023},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:32.680380Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:9eb826bd2441018b29196735655252c722f7a6dfe3a1676a91956765c2204320","observation_id":"4f00ec0a-4b42-47a9-a2ad-f5eba5034d95","resolution":{"observed_at":"2026-08-07T00:23:36.292038Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.06594","last_updated":"2023-03-12T07:22:08Z","snapshot_observed_at":"2026-07-06T15:01:49.803305Z","submitted_at":"2023-03-12T07:22:08Z","title":"ChatGPT Asks, BLIP-2 Answers: Automatic Questioning Towards Enriched Visual Descriptions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.06594","snapshot_observed_at":"2026-08-07T00:23:32.836660Z","title":"Chatgpt asks, blip-2 answers: Automatic questioning towards enriched visual descriptions, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:32.836660Z"},"links":{"cited_paper":"/paper/2303.06594","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:216fb01b310bc9d521cf8b6cc9e1214afac38ffa6afd9dc4935f83fc78b9b754","observation_id":"7d012bea-a758-4e5b-b7e6-288bc1cba0b5","resolution":{"observed_at":"2026-08-07T00:23:32.836660Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.14165","last_updated":"2020-07-22T19:47:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-05-28T17:29:03Z","title":"Language Models are Few-Shot Learners","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14165","snapshot_observed_at":"2026-08-07T00:23:32.995157Z","title":"Language models are few-shot learners","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:32.995157Z"},"links":{"cited_paper":"/paper/2005.14165","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:f5184d53b20076f98df950e1ccdf5ce9eb8765c04d70f9a10105438644bb0585","observation_id":"32ec1b1e-398d-44fd-be06-9ef775484672","resolution":{"observed_at":"2026-08-07T00:23:32.995157Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-07T01:45:38.840969Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-08-07T00:23:33.203526Z","title":"Training verifiers to solve math word problems","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:33.203526Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:31c5407db96250c40fb40d4900b79e1da7eb3e8b195ccb53fa54e5efa80200e7","observation_id":"0954788b-bf76-486d-9c5d-b306f716040b","resolution":{"observed_at":"2026-08-07T00:23:33.203526Z","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":"2026-08-07T00:23:33.397044Z","title":"Measuring mathematical problem solving with the math dataset","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:33.397044Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:78a7a0e9f47f07a0a1c7740276adda6f9bea30c2b5026e3fbc0cb2e1cb79b965","observation_id":"a16d0374-6607-4850-be23-ffa3b0545237","resolution":{"observed_at":"2026-08-07T00:23:33.397044Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.14525","last_updated":"2022-07-29T07:45:56Z","snapshot_observed_at":"2026-07-06T13:36:37.251739Z","submitted_at":"2022-07-29T07:45:56Z","title":"Curriculum Learning for Data-Efficient Vision-Language Alignment","version":1},"cited_work":{"arxiv_id":"2207.14525","doi":null,"metadata_source":"pith","pith_arxiv_id":"2207.14525","snapshot_observed_at":"2026-08-07T00:23:34.532788Z","title":"Curriculum Learning for Data-Efficient Vision-Language Alignment","venue":"cs.CV","work_id":"28c83799-cb80-4261-baa6-fd0f0cb58723","year":2022},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:33.591624Z"},"links":{"cited_paper":"/paper/2207.14525","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:8dc6a72ef629b7d0049139f5f5420b9ba3947730b9f9f946f0cd273139ac6d8c","observation_id":"718c9b81-d977-480c-9672-755c7693d463","resolution":{"observed_at":"2026-08-07T00:23:34.651542Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:23:35.837627Z","title":"PMC Open Access Subset","venue":null,"work_id":"46b8bf36-d34d-421a-a776-c7c72b2578ba","year":2003},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:33.694606Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:fc10efe29426df3e906368579101939ef6a0bf748e7c4d482d610997209bd269","observation_id":"42a278dc-d580-42c9-bf0c-bc8caf2d22ae","resolution":{"observed_at":"2026-08-07T00:23:35.960620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:23:35.486797Z","title":"When scaling meets llm finetuning: The effect of data, model and finetuning method","venue":null,"work_id":"c8804f58-b1d6-420a-81fe-9bc9dec2d322","year":2024},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:33.873751Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:dfb5b9c9c39871ab5202a27417433a93c44540780d4a7493f7ddf74aa1d9fe8c","observation_id":"c7ff8832-b00c-4283-9c0c-11f6eaa9d962","resolution":{"observed_at":"2026-08-07T00:23:35.673139Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"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":"2026-08-07T00:23:34.021746Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:34.021746Z"},"links":{"cited_paper":"/paper/1901.07042","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:ed5b545f530cc349fc6959429c548f5b71d2c713bb4a1548566fffc6fbd65703","observation_id":"3e3b4cb3-70d0-4fbc-abcf-c88da8af3805","resolution":{"observed_at":"2026-08-07T00:23:34.021746Z","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":"2026-08-07T00:23:34.151279Z","title":"Bleu: A method for auto- matic evaluation of machine translation","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:34.151279Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:71967cd0e9815750dcf9848894ab152becc23e88bfbaac178400f51d9c35d20e","observation_id":"f4476fcd-a708-45f0-a359-2255ac72e2d7","resolution":{"observed_at":"2026-08-07T00:23:34.151279Z","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":"2026-08-07T00:23:35.213580Z","title":"\"\" Figure 9: Generate Literature Based Questions Prompt B Evaluation and Saliency Diagnostics def evaluate_generation(generation,ground): prompt = f","venue":null,"work_id":"5b33a100-c5e4-43bb-9efb-a58baff68c7c","year":2004},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:34.251478Z"},"links":{"citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:609ca5c658ef75dc95b3acdb4a9b07f18351145af4d3605ff8d45b6124e59edd","observation_id":"ff2e4bf9-dcfe-475b-9459-33bef2cb4f91","resolution":{"observed_at":"2026-08-07T00:23:35.265017Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.02994","last_updated":"2025-07-17T12:30:16Z","snapshot_observed_at":"2026-07-06T18:40:52.966572Z","submitted_at":"2024-07-03T10:49:21Z","title":"MedPix 2.0: A Comprehensive Multimodal Biomedical Data set for Advanced AI Applications with Retrieval Augmented Generation and Knowledge Graphs","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.02994","snapshot_observed_at":"2026-08-07T00:23:29.392852Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:29.392852Z"},"links":{"cited_paper":"/paper/2407.02994","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:e6a1805c825e977b4522c5f3ee5b5acd05849439f22845be2e18dfdbc28430fe","observation_id":"86b58f7c-bb01-4536-a29c-4e6bcfd0f61f","resolution":{"observed_at":"2026-08-07T00:23:29.392852Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T00:15:16.195875Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering"},"reference_resolution":{"displayed":48,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":27,"verified_exact":1,"verified_fuzzy":20},"total_outbound_references":48},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2506.14451."}