Li, Bei

8 publications

ICLR 2025 Earlier Tokens Contribute More: Learning Direct Preference Optimization from Temporal Decay Perspective Ruichen Shao, Bei Li, Gangao Liu, Yang Chen, ZhouXiang, Jingang Wang, Xunliang Cai, Peng Li

ICML 2025 GRAM: A Generative Foundation Reward Model for Reward Generalization Chenglong Wang, Yang Gan, Yifu Huo, Yongyu Mu, Qiaozhi He, Murun Yang, Bei Li, Tong Xiao, Chunliang Zhang, Tongran Liu, Jingbo Zhu

NeurIPS 2025 MRO: Enhancing Reasoning in Diffusion Language Models via Multi-Reward Optimization Chenglong Wang, Yang Gan, Hang Zhou, Chi Hu, Yongyu Mu, Kai Song, MuRun Yang, Bei Li, Chunliang Zhang, Tongran Liu, JingBo Zhu, Zhengtao Yu, Tong Xiao

ICLR 2024 Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yujiu Yang

AAAI 2024 ESRL: Efficient Sampling-Based Reinforcement Learning for Sequence Generation Chenglong Wang, Hang Zhou, Yimin Hu, Yifu Huo, Bei Li, Tongran Liu, Tong Xiao, Jingbo Zhu

NeurIPS 2024 Predictor-Corrector Enhanced Transformers with Exponential Moving Average Coefficient Learning Bei Li, Tong Zheng, Rui Wang, Jiahao Liu, Qingyan Guo, Junliang Guo, Xu Tan, Tong Xiao, Jingbo Zhu, Jingang Wang, Xunliang Cai

ICML 2022 Learning Multiscale Transformer Models for Sequence Generation Bei Li, Tong Zheng, Yi Jing, Chengbo Jiao, Tong Xiao, Jingbo Zhu

AAAI 2021 Learning Light-Weight Translation Models from Deep Transformer Bei Li, Ziyang Wang, Hui Liu, Quan Du, Tong Xiao, Chunliang Zhang, Jingbo Zhu