Kaixuan Ji
Ph.D. Student in Computer Science, University of California, Los Angeles
Ph.D. Student in Computer Science, University of California, Los Angeles
Reinforcement Learning from Human Feedback with Active Queries
Kaixuan Ji*, Jiafan He*, Quanquan Gu, TMLR 2025, Featured Certification
Self-play Preference Optimization for Language Model Alignment
Yue Wu*, Zhiqing Sun*, Huizhuo Yuan*, Kaixuan Ji, Yiming Yang, Quanquan Gu, ICLR 2025,
Self-play Fine-tuning of Diffusion Models for Text-to-image Generation
Huizhuo Yuan*, Zixiang Chen*, Kaixuan Ji*, Quanquan Gu, NeurIPS 2024
Self-play Fine-tuning Converts Weak Language Models to Strong Language Models
Zixiang Chen*, Yihe Deng*, Huizhuo Yuan*, Kaixuan Ji, Quanquan Gu, ICML 2024
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs
Kaixuan Ji*, Qingyue Zhao*, Jiafan He, Weitong Zhang, Quanquan Gu, ICLR 2024
Parameter-efficient Prompt Tuning Makes Generalized and Calibrated Neural Text Retrievers
Weng Lam Tam*, Xiao Liu*, Kaixuan Ji, Lilong Xue, Xingjian Zhang, Yuxiao Dong, Jiahua Liu, Maodi Hu, Jie Tang, Findings of EMNLP 2023
P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks
Xiao Liu*, Kaixuan Ji*, Yicheng Fu*, Weng Tam, Zhengxiao Du, Zhilin Yang, Jie Tang, ACL 2022
Mastering the Task of Open Information Extraction with Large Language Models and Consistent Reasoning Environment
Ji Qi*, Kaixuan Ji*, Xiaozhi Wang, Jifan Yu, Kaisheng Zeng, Lei Hou, Juanzi Li, Bin Xu, arXiv:2310.10590
Enhancing Multi-Step Reasoning Abilities of Language Models through Direct Q-Function Optimization
Kaixuan Ji*, Guanlin Liu*, Ning Dai, Qingping Yang, Renjie Zheng, Zheng Wu, Chen Dun, Quanquan Gu, Lin Yan, arXiv:2410.09302
Towards a Sharp Analysis of Offline Policy Learning for f-Divergence-Regularized Contextual Bandits
Qingyue Zhao*, Kaixuan Ji*, Heyang Zhao*, Tong Zhang, Quanquan Gu, arXiv:2502.06051.