12 citations · 27 across the 5 of their papers we have counts for
5 papers
Mitigating Object Hallucination in Large Vision-Language Models via Image-Grounded Guidance
Linxi Zhao, Yihe Deng, Weitong Zhang +1
The advancement of Large Vision-Language Models (LVLMs) has increasingly highlighted the critical issue of their tendency to hallucinate non-existing objects in the images. To addr…
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
Zixiang Chen, Yihe Deng, Huizhuo Yuan +2
Harnessing the power of human-annotated data through Supervised Fine-Tuning (SFT) is pivotal for advancing Large Language Models (LLMs). In this paper, we delve into the prospect o…
Risk Bounds of Accelerated SGD for Overparameterized Linear Regression
Xuheng Li, Yihe Deng, Jingfeng Wu +2
Accelerated stochastic gradient descent (ASGD) is a workhorse in deep learning and often achieves better generalization performance than SGD. However, existing optimization theory…
Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves
Yihe Deng, Weitong Zhang, Zixiang Chen +1
Misunderstandings arise not only in interpersonal communication but also between humans and Large Language Models (LLMs). Such discrepancies can make LLMs interpret seemingly unamb…
Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP
Zixiang Chen, Yihe Deng, Yuanzhi Li +1
Multi-modal learning has become increasingly popular due to its ability to leverage information from different data sources (e.g., text and images) to improve the model performance…