Jiang, Haoming

27 publications

NeurIPS 2025 Ask a Strong LLM Judge When Your Reward Model Is Uncertain Zhenghao Xu, Qin Lu, Qingru Zhang, Liang Qiu, Ilgee Hong, Changlong Yu, Wenlin Yao, Yao Liu, Haoming Jiang, Lihong Li, Hyokun Yun, Tuo Zhao

ICML 2025 Discriminative Finetuning of Generative Large Language Models Without Reward Models and Human Preference Data Siqi Guo, Ilgee Hong, Vicente Balmaseda, Changlong Yu, Liang Qiu, Xin Liu, Haoming Jiang, Tuo Zhao, Tianbao Yang

NeurIPS 2025 Think-RM: Enabling Long-Horizon Reasoning in Generative Reward Models Ilgee Hong, Changlong Yu, Liang Qiu, Weixiang Yan, Zhenghao Xu, Haoming Jiang, Qingru Zhang, Qin Lu, Xin Liu, Chao Zhang, Tuo Zhao

TMLR 2025 Two-Step Offline Preference-Based Reinforcement Learning on Explicitly Constrained Policies Yinglun Xu, Tarun Suresh, Rohan Gumaste, David Zhu, Ruirui Li, Zhengyang Wang, Haoming Jiang, Xianfeng Tang, Qingyu Yin, Monica Xiao Cheng, Qi Zeng, Chao Zhang, Gagandeep Singh

NeurIPS 2024 Adaptive Preference Scaling for Reinforcement Learning with Human Feedback Ilgee Hong, Zichong Li, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao

ICML 2024 MEMORYLLM: Towards Self-Updatable Large Language Models Yu Wang, Yifan Gao, Xiusi Chen, Haoming Jiang, Shiyang Li, Jingfeng Yang, Qingyu Yin, Zheng Li, Xian Li, Bing Yin, Jingbo Shang, Julian Mcauley

ICMLW 2024 RNR: Teaching Large Language Models to Follow Roles and Rules Kuan Wang, Alexander Bukharin, Haoming Jiang, Qingyu Yin, Zhengyang Wang, Tuo Zhao, Jingbo Shang, Chao Zhang, Bing Yin, Xian Li, Jianshu Chen, Shiyang Li

NeurIPS 2024 Robust Reinforcement Learning from Corrupted Human Feedback Alexander Bukharin, Ilgee Hong, Haoming Jiang, Zichong Li, Qingru Zhang, Zixuan Zhang, Tuo Zhao

NeurIPS 2023 Amazon-M2: A Multilingual Multi-Locale Shopping Session Dataset for Recommendation and Text Generation Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang

NeurIPSW 2023 DiP-GNN: Discriminative Pre-Training of Graph Neural Networks Simiao Zuo, Haoming Jiang, Qingyu Yin, Xianfeng Tang, Bing Yin, Tuo Zhao

ICLR 2023 HomoDistil: Homotopic Task-Agnostic Distillation of Pre-Trained Transformers Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bing Yin, Tuo Zhao

ICML 2023 SMURF-THP: Score Matching-Based UnceRtainty quantiFication for Transformer Hawkes Process Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang, Tuo Zhao, Hongyuan Zha

LoG 2022 AutoGDA: Automated Graph Data Augmentation for Node Classification Tong Zhao, Xianfeng Tang, Danqing Zhang, Haoming Jiang, Nikhil Rao, Yiwei Song, Pallav Agrawal, Karthik Subbian, Bing Yin, Meng Jiang

NeurIPSW 2022 Condensing Graphs via One-Step Gradient Matching Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin

ICLR 2022 No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao

AISTATS 2021 Learning to Defend by Learning to Attack Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao

ICML 2020 Deep Reinforcement Learning with Robust and Smooth Policy Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao

ICLR 2020 On the Variance of the Adaptive Learning Rate and Beyond Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han

ICML 2020 Transformer Hawkes Process Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha

NeurIPS 2019 Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao

ICLRW 2019 Learning to Defense by Learning to Attack Zhehui Chen, Haoming Jiang, Yuyang Shi, Bo Dai, Tuo Zhao

NeurIPS 2019 Meta Learning with Relational Information for Short Sequences Yujia Xie, Haoming Jiang, Feng Liu, Tuo Zhao, Hongyuan Zha

ICLR 2019 On Computation and Generalization of Generative Adversarial Networks Under Spectrum Control Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao

UAI 2019 On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don’t Worry About Its Nonsmooth Loss Function Xinguo Li, Haoming Jiang, Jarvis Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao

ICML 2019 On Scalable and Efficient Computation of Large Scale Optimal Transport Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha

ICLRW 2019 On Scalable and Efficient Computation of Large Scale Optimal Transport Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha

MLOSS 2019 Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao