6 citations · 6 across the 6 of their papers we have counts for
6 papers
Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges
Xiaohua Wang, Muzhao Tian, Yuqi Zeng +20
Reinforcement Learning from Human Feedback (RLHF) and related alignment paradigms have become central to steering large language models (LLMs) and multimodal large language models…
VIB-Probe: Detecting and Mitigating Hallucinations in Vision-Language Models via Variational Information Bottleneck
Feiran Zhang, Yixin Wu, Zhenghua Wang +4
Vision-Language Models (VLMs) have demonstrated remarkable progress in multimodal tasks, but remain susceptible to hallucinations, where generated text deviates from the underlying…
Explainable Synthetic Image Detection through Diffusion Timestep Ensembling
Yixin Wu, Feiran Zhang, Tianyuan Shi +7
Recent advances in diffusion models have enabled the creation of deceptively real images, posing significant security risks when misused. In this study, we empirically show that di…
Enhancing the Capability and Robustness of Large Language Models through Reinforcement Learning-Driven Query Refinement
Xiaohua Wang, Zisu Huang, Feiran Zhang +5
The capacity of large language models (LLMs) to generate honest, harmless, and helpful responses heavily relies on the quality of user prompts. However, these prompts often tend to…
Searching for Best Practices in Retrieval-Augmented Generation
Xiaohua Wang, Zhenghua Wang, Xuan Gao +11
Retrieval-augmented generation (RAG) techniques have proven to be effective in integrating up-to-date information, mitigating hallucinations, and enhancing response quality, partic…
Towards Biologically Plausible Computing: A Comprehensive Comparison
Changze Lv, Yufei Gu, Zhengkang Guo +16
Backpropagation is a cornerstone algorithm in training neural networks for supervised learning, which uses a gradient descent method to update network weights by minimizing the dis…