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Medical Visual Question Answering

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Showing 1–25 of 97 papers

TitleStatusHype
Barriers in Integrating Medical Visual Question Answering into Radiology Workflows: A Scoping Review and Clinicians' Insights—0
SMMILE: An Expert-Driven Benchmark for Multimodal Medical In-Context Learning—0
GEMeX-ThinkVG: Towards Thinking with Visual Grounding in Medical VQA via Reinforcement Learning—0
CAPO: Reinforcing Consistent Reasoning in Medical Decision-Making—0
Kvasir-VQA-x1: A Multimodal Dataset for Medical Reasoning and Robust MedVQA in Gastrointestinal EndoscopyCode0
MedOrch: Medical Diagnosis with Tool-Augmented Reasoning Agents for Flexible Extensibility—0
A Causal Approach to Mitigate Modality Preference Bias in Medical Visual Question Answering—0
Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models—0
MedAgentBoard: Benchmarking Multi-Agent Collaboration with Conventional Methods for Diverse Medical TasksCode1
Structure Causal Models and LLMs Integration in Medical Visual Question Answering—0
Bridging the Semantic Gaps: Improving Medical VQA Consistency with LLM-Augmented Question Sets—0
Hierarchical Modeling for Medical Visual Question Answering with Cross-Attention Fusion—0
Vision-Amplified Semantic Entropy for Hallucination Detection in Medical Visual Question Answering—0
DiN: Diffusion Model for Robust Medical VQA with Semantic Noisy Labels—0
ClinKD: Cross-Modal Clinical Knowledge Distiller For Multi-Task Medical ImagesCode0
Alignment, Mining and Fusion: Representation Alignment with Hard Negative Mining and Selective Knowledge Fusion for Medical Visual Question Answering—0
MedCoT: Medical Chain of Thought via Hierarchical ExpertCode1
BiMediX2: Bio-Medical EXpert LMM for Diverse Medical ModalitiesCode2
GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-ray Diagnosis—0
Med-2E3: A 2D-Enhanced 3D Medical Multimodal Large Language Model—0
A Survey of Medical Vision-and-Language Applications and Their TechniquesCode1
Efficient Bilinear Attention-based Fusion for Medical Visual Question Answering—0
R-LLaVA: Improving Med-VQA Understanding through Visual Region of Interest—0
Which Client is Reliable?: A Reliable and Personalized Prompt-based Federated Learning for Medical Image Question Answering—0
LLaVA-Ultra: Large Chinese Language and Vision Assistant for Ultrasound—0
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