1 citations · 2 across the 35 of their papers we have counts for
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Preference Alignment for Diffusion Model via Explicit Denoised Distribution Estimation
Dingyuan Shi, Yong Wang, Hangyu Li +1
Diffusion models have shown remarkable success in text-to-image generation, making preference alignment for these models increasingly important. The preference labels are typically…
MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective
Hailang Huang, Yong Wang, Zixuan Huang +4
Large Multimodal Models (LMMs) demonstrate impressive capabilities. However, current benchmarks predominantly focus on image comprehension in specific domains, and these benchmarks…
Textualized Agent-Style Reasoning for Complex Tasks by Multiple Round LLM Generation
Chen Liang, Zhifan Feng, Zihe Liu +4
Chain-of-thought prompting significantly boosts the reasoning ability of large language models but still faces three issues: hallucination problem, restricted interpretability, and…
Direct Alignment of Language Models via Quality-Aware Self-Refinement
Runsheng Yu, Yong Wang, Xiaoqi Jiao +2
Reinforcement Learning from Human Feedback (RLHF) has been commonly used to align the behaviors of Large Language Models (LLMs) with human preferences. Recently, a popular alternat…
Adaptive Task Balancing for Visual Instruction Tuning via Inter-Task Contribution and Intra-Task Difficulty
Yanqi Dai, Yong Wang, Zebin You +3
Visual instruction tuning is a key training stage of large multimodal models. However, when learning multiple visual tasks simultaneously, this approach often results in suboptimal…