3 papers
cs.AI2026
Why Does Grounding Hurt Medical VQA? Benchmarking, Diagnosis, and Fine-Tuning of Vision-Language Models
Xupeng Chen, Binbin Shi, Chenqian Le +5
Vision-language models (VLMs) are increasingly applied to medical visual question answering (Med-VQA), yet whether they can \emph{localize} the evidence behind their answers---a pr…
cs.CL2025
Instruction Tuning and CoT Prompting for Contextual Medical QA with LLMs
Chenqian Le, Ziheng Gong, Chihang Wang +3
Large language models (LLMs) have shown great potential in medical question answering (MedQA), yet adapting them to biomedical reasoning remains challenging due to domain-specific…
cs.LG2024
Enhancing Exchange Rate Forecasting with Explainable Deep Learning Models
Shuchen Meng, Andi Chen, Chihang Wang +5
Accurate exchange rate prediction is fundamental to financial stability and international trade, positioning it as a critical focus in economic and financial research. Traditional…