Hanze Dong

According to our database, Hanze Dong authored at least 45 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

BOLT: Bootstrap Long Chain-of-Thought in Language Models without Distillation.

Bo Pang, Hanze Dong, Jiacheng Xu, Silvio Savarese, Yingbo Zhou, Caiming Xiong

CoRR, February, 2025

Reward-Guided Speculative Decoding for Efficient LLM Reasoning.

Baohao Liao, Yuhui Xu, Hanze Dong, Junnan Li, Christof Monz, Silvio Savarese, Doyen Sahoo, Caiming Xiong

CoRR, January, 2025

2024

Offline Reinforcement Learning for LLM Multi-Step Reasoning.

Huaijie Wang, Shibo Hao, Hanze Dong, Shenao Zhang, Yilin Bao, Ziran Yang, Yi Wu

CoRR, 2024

Entropy-Regularized Process Reward Model.

Hanning Zhang, Pengcheng Wang, Shizhe Diao, Yong Lin, Rui Pan, Hanze Dong, Dylan Zhang, Pavlo Molchanov, Tong Zhang

CoRR, 2024

Automatic Curriculum Expert Iteration for Reliable LLM Reasoning.

Zirui Zhao, Hanze Dong, Amrita Saha, Caiming Xiong, Doyen Sahoo

CoRR, 2024

MathHay: An Automated Benchmark for Long-Context Mathematical Reasoning in LLMs.

Lei Wang, Shan Dong, Yuhui Xu, Hanze Dong, Yalu Wang, Amrita Saha, Ee-Peng Lim, Caiming Xiong, Doyen Sahoo

CoRR, 2024

ThinK: Thinner Key Cache by Query-Driven Pruning.

Yuhui Xu, Zhanming Jie, Hanze Dong, Lei Wang, Xudong Lu, Aojun Zhou, Amrita Saha, Caiming Xiong, Doyen Sahoo

CoRR, 2024

RLHF Workflow: From Reward Modeling to Online RLHF.

Hanze Dong, Wei Xiong, Bo Pang, Haoxiang Wang, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang

CoRR, 2024

An Improved Analysis of Langevin Algorithms with Prior Diffusion for Non-Log-Concave Sampling.

Xunpeng Huang, Hanze Dong, Difan Zou, Tong Zhang

CoRR, 2024

MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance.

Renjie Pi, Tianyang Han, Yueqi Xie, Rui Pan, Qing Lian, Hanze Dong, Jipeng Zhang, Tong Zhang

CoRR, 2024

Enhancing Multi-modal Regular Expression Synthesis via Large Language Models and Semantic Manipulations of Sub-expressions.

Zipan Tang, Yixuan Yan, Rongchen Li, Hanze Dong, Haiming Chen, Hongyu Gao

Proceedings of the Dependable Software Engineering. Theories, Tools, and Applications, 2024

Online Iterative Reinforcement Learning from Human Feedback with General Preference Model.

Chenlu Ye, Wei Xiong, Yuheng Zhang, Hanze Dong, Nan Jiang, Tong Zhang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference.

Xunpeng Huang, Difan Zou, Hanze Dong, Yi Zhang, Yian Ma, Tong Zhang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models.

Shizhe Diao, Rui Pan, Hanze Dong, Kashun Shum, Jipeng Zhang, Wei Xiong, Tong Zhang

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: System Demonstrations, 2024

Faster Sampling via Stochastic Gradient Proximal Sampler.

Xunpeng Huang, Difan Zou, Hanze Dong, Yian Ma, Tong Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint.

Wei Xiong, Hanze Dong, Chenlu Ye, Ziqi Wang, Han Zhong, Heng Ji, Nan Jiang, Tong Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Spurious Feature Diversification Improves Out-of-distribution Generalization.

Yong Lin, Lu Tan, Yifan Hao, Honam Wong, Hanze Dong, Weizhong Zhang, Yujiu Yang, Tong Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Reverse Diffusion Monte Carlo.

Xunpeng Huang, Hanze Dong, Yifan Hao, Yian Ma, Tong Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

FIRST: Teach A Reliable Large Language Model Through Efficient Trustworthy Distillation.

KaShun Shum, Minrui Xu, Jianshu Zhang, Zixin Chen, Shizhe Diao, Hanze Dong, Jipeng Zhang, Muhammad Omer Raza

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance.

Renjie Pi, Tianyang Han, Jianshu Zhang, Yueqi Xie, Rui Pan, Qing Lian, Hanze Dong, Jipeng Zhang, Tong Zhang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Mitigating the Alignment Tax of RLHF.

Yong Lin, Hangyu Lin, Wei Xiong, Shizhe Diao, Jianmeng Liu, Jipeng Zhang, Rui Pan, Haoxiang Wang, Wenbin Hu, Hanning Zhang, Hanze Dong, Renjie Pi, Han Zhao, Nan Jiang, Heng Ji, Yuan Yao, Tong Zhang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Faster Sampling without Isoperimetry via Diffusion-based Monte Carlo.

Xunpeng Huang, Difan Zou, Hanze Dong, Yi-An Ma, Tong Zhang

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment.

Hanze Dong, Wei Xiong, Deepanshu Goyal, Yihan Zhang, Winnie Chow, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, Tong Zhang

Trans. Mach. Learn. Res., 2023

Gibbs Sampling from Human Feedback: A Provable KL- constrained Framework for RLHF.

Wei Xiong, Hanze Dong, Chenlu Ye, Han Zhong, Nan Jiang, Tong Zhang

CoRR, 2023

Mitigating the Alignment Tax of RLHF.

Yong Lin, Hangyu Lin, Wei Xiong, Shizhe Diao, Jianmeng Liu, Jipeng Zhang, Rui Pan, Haoxiang Wang, Wenbin Hu, Hanning Zhang, Hanze Dong, Renjie Pi, Han Zhao, Nan Jiang, Yuan Yao, Tong Zhang

CoRR, 2023

Monte Carlo Sampling without Isoperimetry: A Reverse Diffusion Approach.

Xunpeng Huang, Hanze Dong, Yifan Hao, Yian Ma, Tong Zhang

CoRR, 2023

RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment.

Hanze Dong, Wei Xiong, Deepanshu Goyal, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, Tong Zhang

CoRR, 2023

Provable Particle-based Primal-Dual Algorithm for Mixed Nash Equilibrium.

Shihong Ding, Hanze Dong, Cong Fang, Zhouchen Lin, Tong Zhang

CoRR, 2023

Particle-based Variational Inference with Preconditioned Functional Gradient Flow.

Hanze Dong, Xi Wang, Yong Lin, Tong Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

DetGPT: Detect What You Need via Reasoning.

Renjie Pi, Jiahui Gao, Shizhe Diao, Rui Pan, Hanze Dong, Jipeng Zhang, Lewei Yao, Jianhua Han, Hang Xu, Lingpeng Kong, Tong Zhang

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Catalyst Acceleration of Error Compensated Methods Leads to Better Communication Complexity.

Xun Qian, Hanze Dong, Tong Zhang, Peter Richtárik

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Weakly Supervised Disentangled Generative Causal Representation Learning.

Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang

J. Mach. Learn. Res., 2022

Learning the Compositional Domains for Generalized Zero-shot Learning.

Hanze Dong, Yanwei Fu, Sung Ju Hwang, Leonid Sigal, Xiangyang Xue

Comput. Vis. Image Underst., 2022

Normalizing Flow with Variational Latent Representation.

Hanze Dong, Shizhe Diao, Weizhong Zhang, Tong Zhang

CoRR, 2022

How Powerful is Implicit Denoising in Graph Neural Networks.

Songtao Liu, Rex Ying, Hanze Dong, Lu Lin, Jinghui Chen, Dinghao Wu

CoRR, 2022

Local Augmentation for Graph Neural Networks.

Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu

Proceedings of the International Conference on Machine Learning, 2022

Bayesian Invariant Risk Minimization.

Yong Lin, Hanze Dong, Hao Wang, Tong Zhang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Mathematical Models of Overparameterized Neural Networks.

Cong Fang, Hanze Dong, Tong Zhang

Proc. IEEE, 2021

Local Augmentation for Graph Neural Networks.

Songtao Liu, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu

CoRR, 2021

2020

Vocabulary-Informed Zero-Shot and Open-Set Learning.

Yanwei Fu, Xiaomei Wang, Hanze Dong, Yu-Gang Jiang, Meng Wang, Xiangyang Xue, Leonid Sigal

IEEE Trans. Pattern Anal. Mach. Intell., 2020

Extreme vocabulary learning.

Hanze Dong, Zhenfeng Sun, Yanwei Fu, Shi Zhong, Zhengjun Zhang, Yu-Gang Jiang

Frontiers Comput. Sci., 2020

Disentangled Generative Causal Representation Learning.

Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang

CoRR, 2020

2019

Higher-order Weighted Graph Convolutional Networks.

Songtao Liu, Lingwei Chen, Hanze Dong, Zihao Wang, Dinghao Wu, Zengfeng Huang

CoRR, 2019

Over Parameterized Two-level Neural Networks Can Learn Near Optimal Feature Representations.

Cong Fang, Hanze Dong, Tong Zhang

CoRR, 2019

2018

Learning to Separate Domains in Generalized Zero-Shot and Open Set Learning: a probabilistic perspective.

Hanze Dong, Yanwei Fu, Leonid Sigal, Sung Ju Hwang, Yu-Gang Jiang, Xiangyang Xue

CoRR, 2018