{"as_of":"2026-08-09T21:33:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f5abb311d1905a2afbc5c1491bc320c71b0934b0e583f55239b8ed4d7ffb221e","coverage":[{"denominator":33,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:57:22.751107Z","state":"measured"},{"denominator":35,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":35,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-12T19:39:46.922877Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-06-29T23:24:01.588708Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"cited_work":{"arxiv_id":"2506.06600","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.06600","snapshot_observed_at":"2026-06-29T23:24:01.588708Z","title":null,"venue":null,"work_id":"ecf6cccd-4f04-4f58-a415-743a16591c37","year":2025},"citing_paper":{"arxiv_id":"2605.25273","last_updated":"2026-05-24T21:59:32Z","snapshot_observed_at":"2026-07-06T23:35:16.647496Z","submitted_at":"2026-05-24T21:59:32Z","title":"LLM-as-a-Judge in Healthcare: A Scoping Analysis of Applications, Methods, and Human Alignment","version":1},"reference_index":116,"source":"pdf_text","source_observed_at":"2026-06-29T23:18:59.283834Z"},"links":{"cited_paper":"/paper/2506.06600","citing_paper":"/paper/2605.25273"},"observation_digest":"sha256:fffb2a373239121bc653b2046b5d175e20e62d86ca5f6f019ed512d96bcf7131","observation_id":"a7916707-232e-4e32-99ff-9c13587ee46b","resolution":{"observed_at":"2026-06-29T23:24:01.590061Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.06600","snapshot_observed_at":"2026-07-12T19:39:46.922877Z","title":"& Ngo, C","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.05174","last_updated":"2026-04-17T03:08:55Z","snapshot_observed_at":"2026-08-04T02:46:52.030357Z","submitted_at":"2026-04-17T03:08:55Z","title":"Improving Heart-Focused Medical Question Answering in LLMs via Variance-Aware Rubric Rewards with GRPO","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-12T19:39:46.922877Z"},"links":{"cited_paper":"/paper/2506.06600","citing_paper":"/paper/2606.05174"},"observation_digest":"sha256:3339a1bf7d869c5b8b0f2a789cc68dcbe9e3a21af0a84079efe8fad6d1c3a7c8","observation_id":"03ad372f-6803-41f7-bc9d-8f8783da5a6d","resolution":{"observed_at":"2026-07-12T19:39:46.922877Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.06600/citation-record","integrity":"/paper/2506.06600/integrity","json":"/paper/2506.06600/citation-record.json","paper":"/paper/2506.06600"},"outbound":[{"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":"2026-08-07T05:57:22.627032Z","title":"Language models are few-shot learners","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.627032Z"},"links":{"cited_paper":"/paper/2005.14165","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:cbaccac7c03488851efe2a619585c46f06015e7147044698f46337d9ff22ca12","observation_id":"c57bfb3f-f07d-4a98-a200-4525fd253797","resolution":{"observed_at":"2026-08-07T05:57:22.627032Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-07T05:57:22.632278Z","title":"Llama: Open and efficient foundation language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.632278Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:76d29784b904b0828690e6ebf3a559bddff685244f2f038bb3e77010c22ca0a4","observation_id":"20461b7d-3f2e-4d9e-96ff-b7c3c5a2d8d5","resolution":{"observed_at":"2026-08-07T05:57:22.632278Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-07T05:57:22.637181Z","title":"Llama 2: Open foundation and fine-tuned chat models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.637181Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:24573a551aa336d8c6b888cffea03a1f2b873c6fdcd67418290815a5941e2545","observation_id":"21a63095-f6ba-463f-9676-4a004d5f9353","resolution":{"observed_at":"2026-08-07T05:57:22.637181Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-07-06T18:55:11.576666Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-07T05:57:22.641263Z","title":"The llama 3 herd of models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.641263Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:2c7cd4405fc099fb4ec95acba3111cb747d2857e449ceed857d505a2e8ed5b4f","observation_id":"05346d2e-3ece-4cfa-93fd-f83fcabbd77e","resolution":{"observed_at":"2026-08-07T05:57:22.641263Z","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":"2026-08-07T05:57:23.190015Z","title":"Qwen3, April 2025","venue":null,"work_id":"b49aee4b-afe7-44bd-9b3e-56f81370e23b","year":2025},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.646242Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:914289066f42b6778b2793b13ec2ca614b9e933b14c5af597e806380e31baf7f","observation_id":"d355fdae-063a-4c0b-890d-c6dbc462590b","resolution":{"observed_at":"2026-08-07T05:57:23.193547Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:57:23.178816Z","title":"Visual-language models for medical image analysis: A survey","venue":null,"work_id":"94bcba51-d8c1-4b61-922d-ce7a10a4b37d","year":2023},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.650068Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:8c7df262b6f463f0e8fa25117923b5ce988b5c3ce5d5be425815eca549267c6e","observation_id":"a27ca818-e6c9-4536-ba0d-7a5c6713cedd","resolution":{"observed_at":"2026-08-07T05:57:23.182550Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:57:22.654852Z","title":"Med-flamingo: a multimodal medical few-shot learner","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.654852Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:3cef2da8cb82e91606ccea329b4b70d0209de571c3f5db10d142023b10741b24","observation_id":"3d146fbb-eb46-4603-916d-570fde5b3fc8","resolution":{"observed_at":"2026-08-07T05:57:22.654852Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.16994","last_updated":"2024-04-11T03:44:49Z","snapshot_observed_at":"2026-08-02T16:13:55.666519Z","submitted_at":"2024-02-26T20:00:57Z","title":"GEM3D: GEnerative Medial Abstractions for 3D Shape Synthesis","version":2},"cited_work":{"arxiv_id":"2402.16994","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.16994","snapshot_observed_at":"2026-08-07T05:57:22.978669Z","title":"GEM3D: GEnerative Medial Abstractions for 3D Shape Synthesis","venue":"cs.CV","work_id":"60cdcf19-bffb-4aab-8798-81ca02263225","year":2024},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.658151Z"},"links":{"cited_paper":"/paper/2402.16994","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:a0ffa89c7d80530c99bcbee5e5378e917cf7ceb6e9e214331ac5ae2c4235eaa5","observation_id":"22fc5508-addf-460e-b57b-05dff12354d4","resolution":{"observed_at":"2026-08-07T05:57:22.982969Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.00915","last_updated":"2025-01-08T22:58:51Z","snapshot_observed_at":"2026-07-06T14:57:39.647497Z","submitted_at":"2023-03-02T02:20:04Z","title":"BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.00915","snapshot_observed_at":"2026-08-07T05:57:22.662714Z","title":"Biomedclip: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.662714Z"},"links":{"cited_paper":"/paper/2303.00915","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:b3dad297616a9d5a4431086d7638a97f0cb532b667507f98e61bc41398e395c4","observation_id":"e4811ea2-b637-4362-a90f-f8fe9f73e1ad","resolution":{"observed_at":"2026-08-07T05:57:22.662714Z","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":"2026-08-07T05:57:22.666851Z","title":"Biomedgpt: A unified and generalist biomedical generative pre-trained transformer for vision, language, and multimodal tasks","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.666851Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:98f47f795d5c319c60f304843a21f866be6cfdef0f0b6c6ae1a90d80c68df835","observation_id":"b8a46e70-17ed-4b53-9668-28f92aec6133","resolution":{"observed_at":"2026-08-07T05:57:22.666851Z","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":"2026-08-07T05:57:22.670308Z","title":"Llava-med: Training a large language-and-vision assistant for biomedicine in one day","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.670308Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:1182b331eb968ff51cc90c2408c757b5cf205a7b4396272c1a3fa708ae621002","observation_id":"621c8906-edb3-44d1-83ca-f6fdc282c21e","resolution":{"observed_at":"2026-08-07T05:57:22.670308Z","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":"2026-08-07T05:57:22.673917Z","title":"Mimic-cxr, a de-identified publicly available database of chest radiographs with free-text reports","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.673917Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:fea88df06699fc1478251b491b9ab824a7883ae98b288071fafaa9bea739842e","observation_id":"48f93aba-269a-4d53-b74d-ce843f717b7f","resolution":{"observed_at":"2026-08-07T05:57:22.673917Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.07890","last_updated":"2023-12-27T03:36:29Z","snapshot_observed_at":"2026-08-05T09:44:53.829553Z","submitted_at":"2023-05-13T10:27:29Z","title":"Robust Kalman Filters Based on the Sub-Gaussian $\\alpha$-stable Distribution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.07890","snapshot_observed_at":"2026-08-07T05:57:22.677585Z","title":"Pmc-15m: A large-scale dataset for medical vision-language pretraining","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.677585Z"},"links":{"cited_paper":"/paper/2305.07890","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:9e67b8d1eb4b28894146e56d7c67b2a26f5be455a83b2e1e9cacbc3bfb2df5ee","observation_id":"1aad558e-94e1-447e-bc96-998d294aecf9","resolution":{"observed_at":"2026-08-07T05:57:22.677585Z","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":"2026-08-07T05:57:23.137924Z","title":"Artificial intelligence in radiology","venue":null,"work_id":"91494111-2c6d-4c6d-905d-8163f6930936","year":2018},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.681298Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:9a4a50dd66c257fbaed307ea25090c5c27802465632a089d3a799bd96a849eb5","observation_id":"fca66905-e254-4a17-a9af-fc70bf6fc588","resolution":{"observed_at":"2026-08-07T05:57:23.142062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.19634","last_updated":"2025-03-19T13:55:33Z","snapshot_observed_at":"2026-08-07T20:37:56.716831Z","submitted_at":"2025-02-26T23:57:34Z","title":"MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.19634","snapshot_observed_at":"2026-08-07T05:57:22.684656Z","title":"Medvlm-r1: Incentivizing medical reasoning capability of vision-language models (vlms) via reinforcement learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.684656Z"},"links":{"cited_paper":"/paper/2502.19634","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:bfb608d237223b10ebbdff76baa7753ac302ccf1917e1777e267bd8cb7c00c3c","observation_id":"6349b17c-70c1-4041-a3ed-97f290a22c00","resolution":{"observed_at":"2026-08-07T05:57:22.684656Z","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":"2026-08-07T05:57:22.688075Z","title":"Med-r1: Reinforce- ment learning for generalizable medical reasoning in vision-language models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.688075Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:e1d0e8b767e764876f8ad2e2a7080be236288b1db441d3261f2250962d224d5d","observation_id":"eeb376da-144c-4f9e-bf4e-0ecab4f05ec3","resolution":{"observed_at":"2026-08-07T05:57:22.688075Z","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":"2026-08-07T05:57:23.126153Z","title":"Explainability for artificial intelligence in healthcare: a multidisciplinary perspective","venue":null,"work_id":"1a81ca07-5567-4d03-a48e-8cebceff060c","year":2020},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.691442Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:cc7feb4eb867205eafd3c970a3379d677ba039e40710e91112774f34be95618c","observation_id":"d591a105-dcc3-4bbb-b57a-fa8afe9d2838","resolution":{"observed_at":"2026-08-07T05:57:23.130793Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:57:23.114658Z","title":"Chain-of-thought prompting elicits reasoning in large language models","venue":null,"work_id":"32680cc2-68d9-426b-a5f0-f4d1d4960838","year":2022},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.695048Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:d9ede5b2127aedd2759b3798afdcb259fed51dbe997a9d4838d1c310366f02dc","observation_id":"dd1ecbe9-32cb-47c8-b2ae-cec7f1c9e7aa","resolution":{"observed_at":"2026-08-07T05:57:23.118859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.13736","last_updated":"2024-12-18T11:14:02Z","snapshot_observed_at":"2026-08-09T11:47:38.188234Z","submitted_at":"2024-12-18T11:14:02Z","title":"MedCoT: Medical Chain of Thought via Hierarchical Expert","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.13736","snapshot_observed_at":"2026-08-07T05:57:22.698599Z","title":"Medcot: Medical chain of thought via hierarchical expert","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.698599Z"},"links":{"cited_paper":"/paper/2412.13736","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:2ffed14655d61b97140ad13d23dd25ca129c86b991603bca4a8599a0460e0a4d","observation_id":"c2ab2436-87e7-4f78-94c6-47d7493cd9ed","resolution":{"observed_at":"2026-08-07T05:57:22.698599Z","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":"2026-08-07T05:57:23.100179Z","title":"Silvar-med: A speech-driven visual language model for explainable abnormality detection in medical imaging","venue":null,"work_id":"b693967f-cc40-4178-9ea8-8d60570e61e8","year":2025},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.702267Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:b61e9c26f84ea4f5cbaf47178bf35f0b6c8698baa4240ab55653405e5292c407","observation_id":"b0fc92e6-b2f7-47af-b297-9e93e147bed8","resolution":{"observed_at":"2026-08-07T05:57:23.105655Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.08912","last_updated":"2024-01-17T01:54:24Z","snapshot_observed_at":"2026-07-06T17:16:34.085999Z","submitted_at":"2024-01-17T01:54:24Z","title":"Two-Stage Estimation and Variance Modeling for Latency-Constrained Variational Quantum Algorithms","version":1},"cited_work":{"arxiv_id":"2401.08912","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.08912","snapshot_observed_at":"2026-08-07T05:57:22.839800Z","title":"Two-Stage Estimation and Variance Modeling for Latency-Constrained Variational Quantum Algorithms","venue":"math.OC","work_id":"a4c38a3d-5fa4-4c00-9cd6-cdbb0260b032","year":2024},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.706142Z"},"links":{"cited_paper":"/paper/2401.08912","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:e308ba0a4acfc5aaa5c6f5f1e9f1a126580e708dfd8d879c024d2ec95bc0080b","observation_id":"c1813c07-a182-4df5-af8e-fb5791917559","resolution":{"observed_at":"2026-08-07T05:57:22.845736Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:57:23.088703Z","title":"Reinforcement learning for medical image analysis: Current progress and future directions","venue":null,"work_id":"2a67d942-64e4-4d90-a40f-f9ad27fc1920","year":2024},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.710524Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:919de34c7a7c5852c298251bb081c0454a6a9fcce33cc63e6faa1741773bd8d9","observation_id":"0f22b2dd-101a-4481-9ea9-42dce54c8cf9","resolution":{"observed_at":"2026-08-07T05:57:23.092508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.09876","last_updated":"2024-03-14T21:13:38Z","snapshot_observed_at":"2026-07-06T17:44:54.095160Z","submitted_at":"2024-03-14T21:13:38Z","title":"Which shapes can appear in a Curve Shortening Flow Singularity?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.09876","snapshot_observed_at":"2026-08-07T05:57:22.713892Z","title":"Generalized reward-driven policy optimization for vision-language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.713892Z"},"links":{"cited_paper":"/paper/2403.09876","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:e2d21945f7af18da4d88bf6d413e1a296803e3ad11cde79499dae009cf501885","observation_id":"fe64f8fd-0251-4290-99d3-5e70ee5715fa","resolution":{"observed_at":"2026-08-07T05:57:22.713892Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.19280","last_updated":"2024-09-30T06:45:16Z","snapshot_observed_at":"2026-08-06T18:57:51.817317Z","submitted_at":"2024-06-27T15:50:41Z","title":"HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.19280","snapshot_observed_at":"2026-08-07T05:57:22.717492Z","title":"Huatuogpt-vision, towards injecting medical visual knowledge into multimodal llms at scale","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.717492Z"},"links":{"cited_paper":"/paper/2406.19280","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:f3d95f9efec374cac7f6510320662bf8740115142ce612bd21ce5d8e3fd2a678","observation_id":"a3f3f9be-363b-4006-9834-d829cd011408","resolution":{"observed_at":"2026-08-07T05:57:22.717492Z","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":"2026-08-07T05:57:22.721052Z","title":"A dataset of clinically generated visual questions and answers about radiology images","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.721052Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:426f8bbbd7d5719d0f18ce4f15c51a4f95be13b9deeea3e741201a995ee308e6","observation_id":"34f1c314-0099-4ed5-96ae-1d085cc868c4","resolution":{"observed_at":"2026-08-07T05:57:22.721052Z","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":"2026-08-07T05:57:22.724573Z","title":"Slake: A semantically- labeled knowledge-enhanced dataset for medical visual question answering","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.724573Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:ad4043e20e4964e24cc80ff0239200558f3679bd7ab976083cc208a2aca19561","observation_id":"0758ad61-c5fa-4d6f-b6c8-001ca2c3f319","resolution":{"observed_at":"2026-08-07T05:57:22.724573Z","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":"2026-08-07T05:57:23.070588Z","title":"Hasan, Vivek V","venue":null,"work_id":"ebc4142e-9cbe-41da-988f-3c266493b5d6","year":2019},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.728235Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:27a8e67b44d8b22871482e217b3c98baf1c3580697ca70a9e632e8188164d047","observation_id":"8c7b02f2-f134-4049-86c5-81af31d62f94","resolution":{"observed_at":"2026-08-07T05:57:23.074082Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03300","last_updated":"2024-04-27T15:25:53Z","snapshot_observed_at":"2026-08-06T14:58:42.911363Z","submitted_at":"2024-02-05T18:55:32Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.03300","snapshot_observed_at":"2026-08-07T05:57:22.731580Z","title":"Deepseekmath: Pushing the limits of mathematical reasoning in open language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.731580Z"},"links":{"cited_paper":"/paper/2402.03300","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:a7d8a58188f31ce51f1464b5a90f6da75e02be4b5f196e8fc2b55e219f5ad25a","observation_id":"c5d2c434-a1a8-4ce4-aaa3-5290bd92de62","resolution":{"observed_at":"2026-08-07T05:57:22.731580Z","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":"2026-08-07T05:57:23.058999Z","title":"Weinberger, and Yoav Artzi","venue":null,"work_id":"ec5936fe-f125-4a8d-ac65-d0e0ac4ed73f","year":null},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.735194Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:f26090c0d3f2c61171efe96a8331cc34378ac2dc0d65c953fcda649b2a77d6a5","observation_id":"55493f64-ddfc-4e72-b236-94359fc45321","resolution":{"observed_at":"2026-08-07T05:57:23.063149Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:57:22.742808Z","title":"Flashattention: Fast and memory-efficient exact attention with io-awareness","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.742808Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:21d6be1532a4fea0d20541d4c51ef8b577c320e54451f7a595c011ae3ece4421","observation_id":"cedffaf2-33a3-4aaf-a605-84f17b598694","resolution":{"observed_at":"2026-08-07T05:57:22.742808Z","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":"2026-08-07T05:57:22.747458Z","title":"Cambrian-1: A fully open, vision-centric exploration of multimodal llms","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.747458Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:68e67ee6422bd5829083999cb1e97fdd3a367b43394594c612ab87db3e249b1f","observation_id":"d107493a-58e3-434b-8b63-5de0e80d7d93","resolution":{"observed_at":"2026-08-07T05:57:22.747458Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.05132","last_updated":"2025-03-10T01:52:08Z","snapshot_observed_at":"2026-07-06T20:48:18.268075Z","submitted_at":"2025-03-07T04:21:47Z","title":"R1-Zero's \"Aha Moment\" in Visual Reasoning on a 2B Non-SFT Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.05132","snapshot_observed_at":"2026-08-07T05:57:22.751107Z","title":"aha moment","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.751107Z"},"links":{"cited_paper":"/paper/2503.05132","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:1d58cbf32bb85c969b7de2da50dfb021bb7ab4407bb4145cc56d4d1c04a335b7","observation_id":"a1a0afb0-d962-481f-9147-dd3b48a2456a","resolution":{"observed_at":"2026-08-07T05:57:22.751107Z","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":"2026-08-07T05:57:23.048164Z","title":null,"venue":null,"work_id":"1301c02e-27fa-48e5-b475-f0eca782c351","year":null},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.738698Z"},"links":{"citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:7e580fec97440ee325e98f1a77f632793b9c6185a7c90535aec5fc48f0b2a761","observation_id":"04006296-ec90-4526-8845-f0df9fa6fb01","resolution":{"observed_at":"2026-08-07T05:57:23.051792Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints"},"reference_resolution":{"displayed":33,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":22,"verified_exact":1,"verified_fuzzy":9},"total_outbound_references":33},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 2 inbound Pith citation observations for arXiv:2506.06600."}