2 papers
cs.CV2024
Treat Visual Tokens as Text? But Your MLLM Only Needs Fewer Efforts to See
Zeliang Zhang, Phu Pham, Wentian Zhao +6
By treating visual tokens from visual encoders as text tokens, Multimodal Large Language Models (MLLMs) have achieved remarkable progress across diverse visual understanding tasks,…
cs.CL2024
Efficient Self-Improvement in Multimodal Large Language Models: A Model-Level Judge-Free Approach
Shijian Deng, Wentian Zhao, Yu-Jhe Li +4
Self-improvement in multimodal large language models (MLLMs) is crucial for enhancing their reliability and robustness. However, current methods often rely heavily on MLLMs themsel…