1 citations · 1 across the 2 of their papers we have counts for
4 papers
Do MLLMs Really See It: Reinforcing Visual Attention in Multimodal LLMs
Siqu Ou, Tianrui Wan, Zhiyuan Zhao +2
While chain-of-thought (CoT) reasoning has substantially improved multimodal large language models (MLLMs) on complex reasoning tasks, existing approaches largely rely on long text…
When Seeing Is not Enough: Revealing the Limits of Active Reasoning in MLLMs
Hongcheng Liu, Pingjie Wang, Yuhao Wang +3
Multimodal large language models (MLLMs) have shown strong capabilities across a broad range of benchmarks. However, most existing evaluations focus on passive inference, where mod…
Bridging the Dynamic Perception Gap: Training-Free Draft Chain-of-Thought for Dynamic Multimodal Spatial Reasoning
Siqu Ou, Hongcheng Liu, Pingjie Wang +4
While chains-of-thought (CoT) have advanced complex reasoning in multimodal large language models (MLLMs), existing methods remain confined to text or static visual domains, often…
Med-PMC: Medical Personalized Multi-modal Consultation with a Proactive Ask-First-Observe-Next Paradigm
Hongcheng Liu, Yusheng Liao, Siqv Ou +4
The application of the Multi-modal Large Language Models (MLLMs) in medical clinical scenarios remains underexplored. Previous benchmarks only focus on the capacity of the MLLMs in…