1 citations · 1 across the 5 of their papers we have counts for
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Reasoning-Aligned Perception Decoupling for Scalable Multi-modal Reasoning
Yunhao Gou, Kai Chen, Zhili Liu +5
Recent breakthroughs in reasoning language models have significantly advanced text-based reasoning. On the other hand, Multi-modal Large Language Models (MLLMs) still lag behind, h…
Corrupted but Not Broken: Understanding and Mitigating the Negative Impacts of Corrupted Data in Visual Instruction Tuning
Yunhao Gou, Hansi Yang, Zhili Liu +8
Visual Instruction Tuning (VIT) aims to enhance Multimodal Large Language Models (MLLMs), yet its effectiveness is often compromised by corrupted datasets with issues such as hallu…
Eyes Closed, Safety On: Protecting Multimodal LLMs via Image-to-Text Transformation
Yunhao Gou, Kai Chen, Zhili Liu +6
Multimodal large language models (MLLMs) have shown impressive reasoning abilities. However, they are also more vulnerable to jailbreak attacks than their LLM predecessors. Althoug…
Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuning
Yunhao Gou, Zhili Liu, Kai Chen +6
Instruction tuning of Large Vision-language Models (LVLMs) has revolutionized the development of versatile models with zero-shot generalization across a wide range of downstream vi…