27 citations · 33 across the 11 of their papers we have counts for
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cs.CV2024★ 1 cited
MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding
Fei Wang, Xingyu Fu, James Y. Huang +18
We introduce MuirBench, a comprehensive benchmark that focuses on robust multi-image understanding capabilities of multimodal LLMs. MuirBench consists of 12 diverse multi-image tas…
cs.CV2024
From Introspection to Best Practices: Principled Analysis of Demonstrations in Multimodal In-Context Learning
Nan Xu, Fei Wang, Sheng Zhang +2
Motivated by in-context learning (ICL) capabilities of Large Language Models (LLMs), multimodal LLMs with additional visual modality are also exhibited with similar ICL abilities w…
cs.CV2024★ 2 cited
mDPO: Conditional Preference Optimization for Multimodal Large Language Models
Fei Wang, Wenxuan Zhou, James Y. Huang +4
Direct preference optimization (DPO) has shown to be an effective method for large language model (LLM) alignment. Recent works have attempted to apply DPO to multimodal scenarios…