He, Di

64 publications

NeurIPS 2025 AlphaDecay: Module-Wise Weight Decay for Heavy-Tailed Balancing in LLMs Di He, Songjun Tu, Ajay Jaiswal, Li Shen, Ganzhao Yuan, Shiwei Liu, Lu Yin

ICML 2025 DPO Meets PPO: Reinforced Token Optimization for RLHF Han Zhong, Zikang Shan, Guhao Feng, Wei Xiong, Xinle Cheng, Li Zhao, Di He, Jiang Bian, Liwei Wang

ICLRW 2025 Follow Hamiltonian Leader: An Efficient Energy-Guided Sampling Method Yunfei Teng, Sixin Zhang, Yao Li, Kai Chen, Di He, Qiwei Ye

ICLR 2025 Let the Code LLM Edit Itself When You Edit the Code Zhenyu He, Jun Zhang, Shengjie Luo, Jingjing Xu, Zhi Zhang, Di He

TMLR 2025 The AI Hippocampus: How Far Are We from Human Memory? Zixia Jia, Jiaqi Li, Yipeng Kang, Yuxuan Wang, Tong Wu, Quansen Wang, Xiaobo Wang, Shuyi Zhang, Junzhe Shen, Qing Li, Siyuan Qi, Yitao Liang, Di He, Zilong Zheng, Song-Chun Zhu

NeurIPS 2025 Theoretical Benefit and Limitation of Diffusion Language Model Guhao Feng, Yihan Geng, Jian Guan, Wei Wu, Liwei Wang, Di He

TMLR 2024 3D Molecular Generation via Virtual Dynamics Shuqi Lu, Lin Yao, Xi Chen, Hang Zheng, Di He, Guolin Ke

ICLR 2024 Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness Bohang Zhang, Jingchu Gai, Yiheng Du, Qiwei Ye, Di He, Liwei Wang

NeurIPS 2024 Bridging Geometric States via Geometric Diffusion Bridge Shengjie Luo, Yixian Xu, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang

ICLRW 2024 DOF: Accelerating High-Order Differential Operators with Forward Propagation Ruichen Li, Chuwei Wang, Haotian Ye, Di He, Liwei Wang

ICMLW 2024 DPO Meets PPO: Reinforced Token Optimization for RLHF Han Zhong, Guhao Feng, Wei Xiong, Xinle Cheng, Li Zhao, Di He, Jiang Bian, Liwei Wang

ICML 2024 Do Efficient Transformers Really Save Computation? Kai Yang, Jan Ackermann, Zhenyu He, Guhao Feng, Bohang Zhang, Yunzhen Feng, Qiwei Ye, Di He, Liwei Wang

ICML 2024 GeoMFormer: A General Architecture for Geometric Molecular Representation Learning Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang

ICLR 2024 Hebbian Learning Based Orthogonal Projection for Continual Learning of Spiking Neural Networks Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin

AISTATS 2024 Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamas Sarlos, Thomas Weingarten, Adrian Weller

ICML 2024 Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning Mingqing Xiao, Yixin Zhu, Di He, Zhouchen Lin

ICML 2024 Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation Zhenyu He, Guhao Feng, Shengjie Luo, Kai Yang, Liwei Wang, Jingjing Xu, Zhi Zhang, Hongxia Yang, Di He

ICML 2023 A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests Bohang Zhang, Guhao Feng, Yiheng Du, Di He, Liwei Wang

AISTATS 2023 Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks Huishuai Zhang, Da Yu, Yiping Lu, Di He

CVPR 2023 DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets Haiyang Wang, Chen Shi, Shaoshuai Shi, Meng Lei, Sen Wang, Di He, Bernt Schiele, Liwei Wang

ICLR 2023 Denoising Masked Autoencoders Help Robust Classification QuanLin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang, Liwei Wang, Di He

NeurIPSW 2023 GeoMFormer: A General Architecture for Geometric Molecular Representation Learning Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang

AISTATS 2023 Learning Physics-Informed Neural Networks Without Stacked Back-Propagation Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu

ICLR 2023 One Transformer Can Understand Both 2D & 3D Molecular Data Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He

ICLR 2023 Rethinking the Expressive Power of GNNs via Graph Biconnectivity Bohang Zhang, Shengjie Luo, Liwei Wang, Di He

NeurIPS 2023 Towards Revealing the Mystery Behind Chain of Thought: A Theoretical Perspective Guhao Feng, Bohang Zhang, Yuntian Gu, Haotian Ye, Di He, Liwei Wang

ICLR 2022 Boosting the Certified Robustness of L-Infinity Distance Nets Bohang Zhang, Du Jiang, Di He, Liwei Wang

ICML 2022 HousE: Knowledge Graph Embedding with Householder Parameterization Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang

NeurIPS 2022 Is $l^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network? Chuwei Wang, Shanda Li, Di He, Liwei Wang

NeurIPS 2022 Online Training Through Time for Spiking Neural Networks Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin

NeurIPS 2022 Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective Bohang Zhang, Du Jiang, Di He, Liwei Wang

CVPR 2022 Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu

NeurIPS 2022 Your Transformer May Not Be as Powerful as You Expect Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He

NeurIPS 2021 Do Transformers Really Perform Badly for Graph Representation? Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu

ICML 2021 GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang

ICML 2021 How Could Neural Networks Understand Programs? Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu

ICLR 2021 Rethinking Positional Encoding in Language Pre-Training Guolin Ke, Di He, Tie-Yan Liu

NeurIPS 2021 Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu

ICLR 2021 Taking Notes on the Fly Helps Language Pre-Training Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu

ICML 2021 Towards Certifying L-Infinity Robustness Using Neural Networks with L-Inf-Dist Neurons Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang

IJCAI 2020 I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations Xufang Luo, Qi Meng, Di He, Wei Chen, Yunhong Wang

ICLR 2020 Incorporating BERT into Neural Machine Translation Jinhua Zhu, Yingce Xia, Lijun Wu, Di He, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu

ECCV 2020 Invertible Image Rescaling Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu

ICLR 2020 MACER: Attack-Free and Scalable Robust Training via Maximizing Certified Radius Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang

ICML 2020 On Layer Normalization in the Transformer Architecture Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tieyan Liu

ICLR 2020 Understanding and Improving Transformer from a Multi-Particle Dynamic System Point of View Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun, Bin Dong, Tao Qin, Liwei Wang, Tie-Yan Liu

ICLRW 2020 Understanding and Improving Transformer from a Multi-Particle Dynamic System Point of View. Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun, Bin Dong, Tao Qin, Liwei Wang, Tie-yan Liu

IJCAI 2019 Deliberation Learning for Image-to-Image Translation Tianyu He, Yingce Xia, Jianxin Lin, Xu Tan, Di He, Tao Qin, Zhibo Chen

ICML 2019 Efficient Training of BERT by Progressively Stacking Linyuan Gong, Di He, Zhuohan Li, Tao Qin, Liwei Wang, Tieyan Liu

NeurIPS 2019 Fast Structured Decoding for Sequence Models Zhiqing Sun, Zhuohan Li, Haoqing Wang, Di He, Zi Lin, Zhihong Deng

ICLR 2019 Multilingual Neural Machine Translation with Knowledge Distillation Xu Tan, Yi Ren, Di He, Tao Qin, Zhou Zhao, Tie-Yan Liu

AAAI 2019 Non-Autoregressive Machine Translation with Auxiliary Regularization Yiren Wang, Fei Tian, Di He, Tao Qin, ChengXiang Zhai, Tie-Yan Liu

AAAI 2019 Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input Junliang Guo, Xu Tan, Di He, Tao Qin, Linli Xu, Tie-Yan Liu

ICLR 2019 Representation Degeneration Problem in Training Natural Language Generation Models Jun Gao, Di He, Xu Tan, Tao Qin, Liwei Wang, Tieyan Liu

AAAI 2019 Sentence-Wise Smooth Regularization for Sequence to Sequence Learning ChengYue Gong, Xu Tan, Di He, Tao Qin

AAAI 2019 Tied Transformers: Neural Machine Translation with Shared Encoder and Decoder Yingce Xia, Tianyu He, Xu Tan, Fei Tian, Di He, Tao Qin

ICML 2019 Towards a Deep and Unified Understanding of Deep Neural Models in NLP Chaoyu Guan, Xiting Wang, Quanshi Zhang, Runjin Chen, Di He, Xing Xie

NeurIPS 2018 FRAGE: Frequency-Agnostic Word Representation Chengyue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu

NeurIPS 2018 Layer-Wise Coordination Between Encoder and Decoder for Neural Machine Translation Tianyu He, Xu Tan, Yingce Xia, Di He, Tao Qin, Zhibo Chen, Tie-Yan Liu

ICML 2018 Towards Binary-Valued Gates for Robust LSTM Training Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tieyan Liu

NeurIPS 2017 Decoding with Value Networks for Neural Machine Translation Di He, Hanqing Lu, Yingce Xia, Tao Qin, Liwei Wang, Tie-Yan Liu

NeurIPS 2016 Dual Learning for Machine Translation Di He, Yingce Xia, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, Wei-Ying Ma

IJCAI 2013 A Game-Theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search Di He, Wei Chen, Liwei Wang, Tie-Yan Liu

COLT 2013 A Theoretical Analysis of NDCG Type Ranking Measures Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Tie-Yan Liu