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Paper Citation Record · LEDGER

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models

As of 8 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2505.13973.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.13973 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:43:34.049540Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved39
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c993af9c-0799-4b55-bc75-1b967876b1d8 · outbound

This paper cites online" 'onlinestring :=.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models online" 'onlinestring :=

Reference 1

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Observation 0086c278-2456-4593-9740-5be1e49a590d · outbound

This paper cites write newline.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models write newline

Reference 2

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source=arxiv_source observed=2026-08-07T15:43:30.116351Z digest=sha256:c379f59a7d56bee7931c062dcbd59290f79aa6019e3b3b98d0e33b59f4443fb0

Observation d2625a23-56a5-45cf-900f-5be9c59664b9 · outbound

This paper cites Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning

Reference 3

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source=arxiv_source observed=2026-08-07T15:43:30.245226Z digest=sha256:f11ba802d4a66abd15e356506f6a706ea14194abb011f2305a34d670315ad2cd

Observation e585a3a3-fa6d-4b21-9c28-ec369a8b097a · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T15:43:30.351330Z digest=sha256:7102678696e7b2bd60fcdd838dec0054faa1d60b1a73838609c8fdcc900f2b1f

Observation eca15f64-1a27-4119-821e-080a268450fd · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 5

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Observation 39147750-bcef-4a0f-885f-f886e0ed0be5 · outbound

This paper cites Vision-Language Models Can Self-Improve Reasoning via Reflection.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Vision-Language Models Can Self-Improve Reasoning via Reflection

Reference 6

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Observation 0353c2e0-0333-4069-944a-6ff0ea14d591 · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 7

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Observation 7c12872c-2522-40a6-970b-18415343905b · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 8

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source=arxiv_source observed=2026-08-07T15:43:30.752803Z digest=sha256:64e9c94a1fea292ce0605f035446102490e6c74a79c00f3c367453adbf997262

Observation 66edf0f7-809f-4720-b248-3123724d02d7 · outbound

This paper cites Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models

Reference 9

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Observation 2a0aab34-6632-4de3-b56f-189c9c036697 · outbound

This paper cites The Llama 3 Herd of Models.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models The Llama 3 Herd of Models

Reference 10

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Observation 4cdb0920-2151-4686-94cf-331907972674 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 11

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Observation ccd43bf7-d09b-4d95-9382-1b4d39545788 · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 12

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Observation 2c09e7ae-55fe-4bb5-bc2d-714a569c4bb0 · outbound

This paper cites Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 13

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Observation 98b9ac47-5b2f-41f1-a935-572a3768597d · outbound

This paper cites Mistral 7B.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Mistral 7B

Reference 14

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Observation 9a7f238e-3dc0-49c4-a70a-ea85c494cf12 · outbound

This paper cites LLM Post-Training: A Deep Dive into Reasoning Large Language Models.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models LLM Post-Training: A Deep Dive into Reasoning Large Language Models

Reference 15

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Observation d3224970-441f-48be-9339-575cec1021d1 · outbound

This paper cites BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains

Reference 16

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Observation 3db54ed8-b633-4a5d-8721-1bd9472187d9 · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 17

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Observation c59230b9-8a55-4f08-a5e8-635c00080c36 · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 18

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 2bbb2501-e7b7-4296-9881-50c504fd81a5 · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 19

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Observation ff045b84-e5de-4954-a5aa-fab2900f7ee1 · outbound

This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Understanding R1-Zero-Like Training: A Critical Perspective

Reference 20

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Observation c37a488c-14a6-4e37-930d-03174f64e814 · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 21

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 85bc92cc-e12d-40b5-bf4b-85aacc88b35b · outbound

This paper cites UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning

Reference 22

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Observation 10625c65-f303-48e7-9c90-4ced387d8e12 · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 23

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Observation cc79f665-816d-45ab-98a2-834e7b962796 · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 24

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Observation 8a1e9c79-23c0-470c-9cb4-92c09170525a · outbound

This paper cites Proximal Policy Optimization Algorithms.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Proximal Policy Optimization Algorithms

Reference 25

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source=arxiv_source observed=2026-08-07T15:43:32.491701Z digest=sha256:4065e01c2520e533f90bd9fd521bf824093c96cac876b4321367b94a9cd51ddb

Observation 2d97a5d0-1e19-4bfa-a1dc-496777c6c5cd · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 26

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Observation b69e7c64-86ed-48bb-8779-7f4c0fb824f7 · outbound

This paper cites VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model

Reference 27

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Observation e0ffa0d3-726f-4542-871f-6a653604d65a · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 28

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Observation e21db740-c644-4fd7-bdcd-e6fd90737047 · outbound

This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 29

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Observation 1947b600-f53c-449e-843c-2386d4acd9ef · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 30

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Observation 9a6b834a-b81e-450e-8489-5efb40855b7e · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9e3019e2-026c-4072-bb84-e23a7b886cd7 · outbound

This paper cites GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents

Reference 32

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Observation 06a2df12-52da-4aee-95e4-e9c4a025b307 · outbound

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Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Improve Vision Language Model Chain-of-thought Reasoning

Reference 33

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Observation 45eb7a77-1544-45be-9be2-8045541f163e · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 34

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Observation 66a8f6d7-957d-4702-89d6-8ebcfda7b726 · outbound

This paper cites PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering

Reference 35

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Observation e46c66b0-777a-4121-bda9-b6f6f8947210 · outbound

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Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcement Learning

Reference 36

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source=arxiv_source observed=2026-08-07T15:43:33.729004Z digest=sha256:3ad4e1cee1ae524f0d29cb05ab60da7422139e7483207c15a67dc5d2f25085fc

Observation 4591e73e-4ce8-40f9-ae02-e5d880d8d484 · outbound

This paper cites an unresolved cited work.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models Unresolved cited work

Reference 37

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raw_fallback, observed 2026-08-07T15:43:34.611405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T15:43:33.787424Z digest=sha256:6fa26ee98bdf1ff04fb268a40a7122b33b0079721d6eea72249539f4206f8775

Observation 52a61e03-e4ca-4a96-86a6-fee5261db3a2 · outbound

This paper cites R1-Zero's "Aha Moment" in Visual Reasoning on a 2B Non-SFT Model.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models R1-Zero's "Aha Moment" in Visual Reasoning on a 2B Non-SFT Model

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T15:43:33.968558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:33.968558Z digest=sha256:e84819165a051440a03f7647dfe08c8104113c0dde848e1ab60e2cba87e90e22

Observation 247b3255-68d8-431b-8ceb-1ecf28d49abd · outbound

This paper cites RetinalGPT: A Retinal Clinical Preference Conversational Assistant Powered by Large Vision-Language Models.

Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models RetinalGPT: A Retinal Clinical Preference Conversational Assistant Powered by Large Vision-Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T15:43:34.049540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:34.049540Z digest=sha256:64987ace3bdc071418793ec1f88b973f03ee99324d73cb78bbde9a780c29c558

Pith citing papers

No inbound Pith citation observations are available.