Di He - RankMe

170 papers A* 50A 3B 1Journal 97Unranked 19

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AgentFactory: A Self-Evolving Framework Through Executable Subagent Accumulation and Reuse. CoRR Zhang Zhang, Shuqi Lu, Hongjin Qian, Di He, Zheng Liu
2026	A*	`conf`	Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression. AAAI Jiameng Huang, Baijiong Lin, Guhao Feng, Jierun Chen, Di He, Lu Hou
2026	—	`conf`	Enhancing Auto-regressive Chain-of-Thought through Loop-Aligned Reasoning. EACL (Volume 1: Long Papers) Qifan Yu, Zhenyu He, Sijie Li, Zhou Xun, Jun Zhang, Jingjing Xu, Di He
2026	J	`jnl`	Luminark: Training-free, Probabilistically-Certified Watermarking for General Vision Generative Models. CoRR Jiayi Xu, Zhang Zhang, Yuanrui Zhang, Ruitao Chen, Yixian Xu, Tianyu He, Di He
2026	J	`jnl`	The AI Hippocampus: How Far are We From Human Memory? CoRR 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
2026	J	`jnl`	Towards Solving the Gilbert-Pollak Conjecture via Large Language Models. CoRR Yisi Ke, Tianyu Huang, Yankai Shu, Di He, Jingchu Gai, Liwei Wang
2026	J	`jnl`	Understanding vs. Generation: Navigating Optimization Dilemma in Multimodal Models. CoRR Sen Ye, Mengde Xu, Shuyang Gu, Di He, Liwei Wang, Han Hu
2025	J	`jnl`	A Foundational Generative Model for Breast Ultrasound Image Analysis. CoRR Haojun Yu, Youcheng Li, Nan Zhang, Zihan Niu, Xuantong Gong, Yanwen Luo, Haotian Ye, Siyu He, Quanlin Wu, Wangyan Qin, Mengyuan Zhou, Jie Han, Jia Tao, Ziwei Zhao, Di Dai, Di He, Dong Wang, Binghui Tang, Ling Huo, James Zou, Qingli Zhu, Yong Wang, Liwei Wang
2025	A*	`conf`	Beyond Online Sampling: Bridging Offline-to-Online Alignment via Dynamic Data Transformation for LLMs. EMNLP Zhang Zhang, Guhao Feng, Jian Guan, Di He, Wei Wu
2025	J	`jnl`	Boosting meta-training with base class information for robust few-shot learning. Eng. Appl. Artif. Intell. Weihao Jiang, Guodong Liu, Di He, Kun He
2025	A*	`conf`	DPO Meets PPO: Reinforced Token Optimization for RLHF. ICML Han Zhong, Zikang Shan, Guhao Feng, Wei Xiong, Xinle Cheng, Li Zhao, Di He, Jiang Bian, Liwei Wang
2025	J	`jnl`	Diagnosing and Improving Diffusion Models by Estimating the Optimal Loss Value. CoRR Yixian Xu, Shengjie Luo, Liwei Wang, Di He, Chang Liu
2025	J	`jnl`	Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression. CoRR Jiameng Huang, Baijiong Lin, Guhao Feng, Jierun Chen, Di He, Lu Hou
2025	J	`jnl`	Enhancing Auto-regressive Chain-of-Thought through Loop-Aligned Reasoning. CoRR Qifan Yu, Zhenyu He, Sijie Li, Xun Zhou, Jun Zhang, Jingjing Xu, Di He
2025	—	`conf`	How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs. ACL (Findings) Guhao Feng, Kai Yang, Yuntian Gu, Xinyue Ai, Shengjie Luo, Jiacheng Sun, Di He, Zhenguo Li, Liwei Wang
2025	J	`jnl`	LarvSeg: Exploring Image Classification Data For Large Vocabulary Semantic Segmentation via Category-wise Attentive Classifier. CoRR Haojun Yu, Di Dai, Ziwei Zhao, Di He, Han Hu, Liwei Wang
2025	A*	`conf`	Let the Code LLM Edit Itself When You Edit the Code. ICLR Zhenyu He, Jun Zhang, Shengjie Luo, Jingjing Xu, Zhi Zhang, Di He
2025	J	`jnl`	Playing with Transformer at 30+ FPS via Next-Frame Diffusion. CoRR Xinle Cheng, Tianyu He, Jiayi Xu, Junliang Guo, Di He, Jiang Bian
2025	J	`jnl`	Spin-Adapted Neural Network Wavefunctions in Real Space. CoRR Ruichen Li, Yuzhi Liu, Du Jiang, Yixiao Chen, Xuelan Wen, Wenrui Li, Di He, Liwei Wang, Ji Chen, Weiluo Ren
2025	J	`jnl`	The AI Hippocampus: How Far are We From Human Memory? Trans. Mach. Learn. Res. 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
2025	J	`jnl`	Theoretical Benefit and Limitation of Diffusion Language Model. CoRR Guhao Feng, Yihan Geng, Jian Guan, Wei Wu, Liwei Wang, Di He
2024	J	`jnl`	3D Molecular Generation via Virtual Dynamics. Trans. Mach. Learn. Res. Shuqi Lu, Lin Yao, Xi Chen, Hang Zheng, Di He, Guolin Ke
2024	A*	`conf`	Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness. ICLR Bohang Zhang, Jingchu Gai, Yiheng Du, Qiwei Ye, Di He, Liwei Wang
2024	J	`jnl`	Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness. CoRR Bohang Zhang, Jingchu Gai, Yiheng Du, Qiwei Ye, Di He, Liwei Wang
2024	J	`jnl`	Boosting Meta-Training with Base Class Information for Few-Shot Learning. CoRR Weihao Jiang, Guodong Liu, Di He, Kun He
2024	A*	`conf`	Bridging Geometric States via Geometric Diffusion Bridge. NeurIPS Shengjie Luo, Yixian Xu, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang
2024	J	`jnl`	Bridging Geometric States via Geometric Diffusion Bridge. CoRR Shengjie Luo, Yixian Xu, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang
2024	J	`jnl`	DOF: Accelerating High-order Differential Operators with Forward Propagation. CoRR Ruichen Li, Chuwei Wang, Haotian Ye, Di He, Liwei Wang
2024	J	`jnl`	DPO Meets PPO: Reinforced Token Optimization for RLHF. CoRR Han Zhong, Guhao Feng, Wei Xiong, Li Zhao, Di He, Jiang Bian, Liwei Wang
2024	A*	`conf`	Do Efficient Transformers Really Save Computation? ICML Kai Yang, Jan Ackermann, Zhenyu He, Guhao Feng, Bohang Zhang, Yunzhen Feng, Qiwei Ye, Di He, Liwei Wang
2024	J	`jnl`	Do Efficient Transformers Really Save Computation? CoRR Kai Yang, Jan Ackermann, Zhenyu He, Guhao Feng, Bohang Zhang, Yunzhen Feng, Qiwei Ye, Di He, Liwei Wang
2024	J	`jnl`	End-to-End Crystal Structure Prediction from Powder X-Ray Diffraction. CoRR Qingsi Lai, Lin Yao, Zhifeng Gao, Siyuan Liu, Hongshuai Wang, Shuqi Lu, Di He, Liwei Wang, Cheng Wang, Guolin Ke
2024	A*	`conf`	GeoMFormer: A General Architecture for Geometric Molecular Representation Learning. ICML Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang
2024	J	`jnl`	GeoMFormer: A General Architecture for Geometric Molecular Representation Learning. CoRR Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang
2024	A*	`conf`	Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks. ICLR Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin
2024	J	`jnl`	Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks. CoRR Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin
2024	J	`jnl`	How Numerical Precision Affects Mathematical Reasoning Capabilities of LLMs. CoRR Guhao Feng, Kai Yang, Yuntian Gu, Xinyue Ai, Shengjie Luo, Jiacheng Sun, Di He, Zhenguo Li, Liwei Wang
2024	J	`jnl`	Knowledge-driven AI-generated data for accurate and interpretable breast ultrasound diagnoses. CoRR Haojun Yu, Youcheng Li, Nan Zhang, Zihan Niu, Xuantong Gong, Yanwen Luo, Quanlin Wu, Wangyan Qin, Mengyuan Zhou, Jie Han, Jia Tao, Ziwei Zhao, Di Dai, Di He, Dong Wang, Binghui Tang, Ling Huo, Qingli Zhu, Yong Wang, Liwei Wang
2024	—	`conf`	LarvSeg: Exploring Image Classification Data for Large Vocabulary Semantic Segmentation via Category-Wise Attentive Classifier. PRCV (1) Haojun Yu, Di Dai, Ziwei Zhao, Di He, Han Hu, Liwei Wang
2024	A	`conf`	Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. AISTATS Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller
2024	J	`jnl`	Let the Code LLM Edit Itself When You Edit the Code. CoRR Zhenyu He, Jun Zhang, Shengjie Luo, Jingjing Xu, Zhi Zhang, Di He
2024	J	`jnl`	Online Pseudo-Zeroth-Order Training of Neuromorphic Spiking Neural Networks. CoRR Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin
2024	—	`conf`	REST: Retrieval-Based Speculative Decoding. NAACL-HLT Zhenyu He, Zexuan Zhong, Tianle Cai, Jason D. Lee, Di He
2024	A*	`conf`	Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning. ICML Mingqing Xiao, Yixin Zhu, Di He, Zhouchen Lin
2024	J	`jnl`	Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning. CoRR Mingqing Xiao, Yixin Zhu, Di He, Zhouchen Lin
2024	A*	`conf`	Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation. ICML Zhenyu He, Guhao Feng, Shengjie Luo, Kai Yang, Liwei Wang, Jingjing Xu, Zhi Zhang, Hongxia Yang, Di He
2024	J	`jnl`	Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation. CoRR Zhenyu He, Guhao Feng, Shengjie Luo, Kai Yang, Di He, Jingjing Xu, Zhi Zhang, Hongxia Yang, Liwei Wang
2023	J	`jnl`	3D Molecular Generation via Virtual Dynamics. CoRR Shuqi Lu, Lin Yao, Xi Chen, Hang Zheng, Di He, Guolin Ke
2023	A*	`conf`	A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests. ICML Bohang Zhang, Guhao Feng, Yiheng Du, Di He, Liwei Wang
2023	J	`jnl`	A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests. CoRR Bohang Zhang, Guhao Feng, Yiheng Du, Di He, Liwei Wang
2023	A	`conf`	Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks. AISTATS Huishuai Zhang, Da Yu, Yiping Lu, Di He
2023	J	`jnl`	CORE: Common Random Reconstruction for Distributed Optimization with Provable Low Communication Complexity. CoRR Pengyun Yue, Hanzhen Zhao, Cong Fang, Di He, Liwei Wang, Zhouchen Lin, Song-Chun Zhu
2023	A*	`conf`	DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets. CVPR Haiyang Wang, Chen Shi, Shaoshuai Shi, Meng Lei, Sen Wang, Di He, Bernt Schiele, Liwei Wang
2023	J	`jnl`	DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets. CoRR Haiyang Wang, Chen Shi, Shaoshuai Shi, Meng Lei, Sen Wang, Di He, Bernt Schiele, Liwei Wang
2023	A*	`conf`	Denoising Masked Autoencoders Help Robust Classification. ICLR Quanlin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang, Liwei Wang, Di He
2023	J	`jnl`	Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo. CoRR Ruichen Li, Haotian Ye, Du Jiang, Xuelan Wen, Chuwei Wang, Zhe Li, Xiang Li, Di He, Ji Chen, Weiluo Ren, Liwei Wang
2023	J	`jnl`	Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+. CoRR Shuqi Lu, Zhifeng Gao, Di He, Linfeng Zhang, Guolin Ke
2023	A	`conf`	Learning Physics-Informed Neural Networks without Stacked Back-propagation. AISTATS Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu
2023	J	`jnl`	Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. CoRR Krzysztof Marcin Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamás Sarlós, Thomas Weingarten, Adrian Weller
2023	A*	`conf`	One Transformer Can Understand Both 2D & 3D Molecular Data. ICLR Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He
2023	J	`jnl`	REST: Retrieval-Based Speculative Decoding. CoRR Zhenyu He, Zexuan Zhong, Tianle Cai, Jason D. Lee, Di He
2023	A*	`conf`	Rethinking the Expressive Power of GNNs via Graph Biconnectivity. ICLR Bohang Zhang, Shengjie Luo, Liwei Wang, Di He
2023	J	`jnl`	Rethinking the Expressive Power of GNNs via Graph Biconnectivity. CoRR Bohang Zhang, Shengjie Luo, Liwei Wang, Di He
2023	—	`conf`	Robustness-Aware Word Embedding Improves Certified Robustness to Adversarial Word Substitutions. ACL (Findings) Yibin Wang, Yichen Yang, Di He, Kun He
2023	A*	`conf`	Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective. NeurIPS Guhao Feng, Bohang Zhang, Yuntian Gu, Haotian Ye, Di He, Liwei Wang
2023	J	`jnl`	Towards Revealing the Mystery behind Chain of Thought: a Theoretical Perspective. CoRR Guhao Feng, Bohang Zhang, Yuntian Gu, Haotian Ye, Di He, Liwei Wang
2022	J	`jnl`	Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks. CoRR Huishuai Zhang, Da Yu, Yiping Lu, Di He
2022	J	`jnl`	Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets. CoRR Yu Shi, Shuxin Zheng, Guolin Ke, Yifei Shen, Jiacheng You, Jiyan He, Shengjie Luo, Chang Liu, Di He, Tie-Yan Liu
2022	A*	`conf`	Boosting the Certified Robustness of L-infinity Distance Nets. ICLR Bohang Zhang, Du Jiang, Di He, Liwei Wang
2022	J	`jnl`	Denoising Masked AutoEncoders are Certifiable Robust Vision Learners. CoRR Quanlin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang, Liwei Wang, Di He
2022	—	`conf`	Finding the Dominant Winning Ticket in Pre-Trained Language Models. ACL (Findings) Zhuocheng Gong, Di He, Yelong Shen, Tie-Yan Liu, Weizhu Chen, Dongyan Zhao, Ji-Rong Wen, Rui Yan
2022	A*	`conf`	HousE: Knowledge Graph Embedding with Householder Parameterization. ICML Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang
2022	J	`jnl`	HousE: Knowledge Graph Embedding with Householder Parameterization. CoRR Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang
2022	A*	`conf`	Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network? NeurIPS Chuwei Wang, Shanda Li, Di He, Liwei Wang
2022	J	`jnl`	Is L CoRR Chuwei Wang, Shanda Li, Di He, Liwei Wang
2022	J	`jnl`	Learning Physics-Informed Neural Networks without Stacked Back-propagation. CoRR Di He, Wenlei Shi, Shanda Li, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu
2022	J	`jnl`	METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals. CoRR Payal Bajaj, Chenyan Xiong, Guolin Ke, Xiaodong Liu, Di He, Saurabh Tiwary, Tie-Yan Liu, Paul Bennett, Xia Song, Jianfeng Gao
2022	J	`jnl`	One Transformer Can Understand Both 2D & 3D Molecular Data. CoRR Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Di He, Liwei Wang
2022	A*	`conf`	Online Training Through Time for Spiking Neural Networks. NeurIPS Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin
2022	J	`jnl`	Online Training Through Time for Spiking Neural Networks. CoRR Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin
2022	A*	`conf`	Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective. NeurIPS Bohang Zhang, Du Jiang, Di He, Liwei Wang
2022	J	`jnl`	Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective. CoRR Bohang Zhang, Du Jiang, Di He, Liwei Wang
2022	A*	`conf`	Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart. CVPR Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu
2022	A*	`conf`	Your Transformer May Not be as Powerful as You Expect. NeurIPS Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He
2022	J	`jnl`	Your Transformer May Not be as Powerful as You Expect. CoRR Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He
2021	J	`jnl`	Adversarial Training with Rectified Rejection. CoRR Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu
2021	J	`jnl`	Boosting the Certified Robustness of L-infinity Distance Nets. CoRR Bohang Zhang, Du Jiang, Di He, Liwei Wang
2021	J	`jnl`	Can Vision Transformers Perform Convolution? CoRR Shanda Li, Xiangning Chen, Di He, Cho-Jui Hsieh
2021	J	`jnl`	Do Transformers Really Perform Bad for Graph Representation? CoRR Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu
2021	A*	`conf`	Do Transformers Really Perform Badly for Graph Representation? NeurIPS Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu
2021	J	`jnl`	First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track. CoRR Chengxuan Ying, Mingqi Yang, Shuxin Zheng, Guolin Ke, Shengjie Luo, Tianle Cai, Chenglin Wu, Yuxin Wang, Yanming Shen, Di He
2021	A*	`conf`	GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. ICML Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang
2021	A*	`conf`	How could Neural Networks understand Programs? ICML Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
2021	J	`jnl`	How could Neural Networks understand Programs? CoRR Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
2021	J	`jnl`	LazyFormer: Self Attention with Lazy Update. CoRR Chengxuan Ying, Guolin Ke, Di He, Tie-Yan Liu
2021	J	`jnl`	Less is More: Pre-training a Strong Siamese Encoder Using a Weak Decoder. CoRR Shuqi Lu, Chenyan Xiong, Di He, Guolin Ke, Waleed Malik, Zhicheng Dou, Paul Bennett, Tie-Yan Liu, Arnold Overwijk
2021	—	`conf`	Less is More: Pretrain a Strong Siamese Encoder for Dense Text Retrieval Using a Weak Decoder. EMNLP (1) Shuqi Lu, Di He, Chenyan Xiong, Guolin Ke, Waleed Malik, Zhicheng Dou, Paul Bennett, Tie-Yan Liu, Arnold Overwijk
2021	A*	`conf`	Rethinking Positional Encoding in Language Pre-training. ICLR Guolin Ke, Di He, Tie-Yan Liu
2021	J	`jnl`	Revisiting Language Encoding in Learning Multilingual Representations. CoRR Shengjie Luo, Kaiyuan Gao, Shuxin Zheng, Guolin Ke, Di He, Liwei Wang, Tie-Yan Liu
2021	A*	`conf`	Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. NeurIPS Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu
2021	J	`jnl`	Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. CoRR Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu
2021	A*	`conf`	Taking Notes on the Fly Helps Language Pre-Training. ICLR Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
2021	—	`conf`	The Open Catalyst Challenge 2021: Competition Report. NeurIPS (Competition and Demos) Abhishek Das, Muhammed Shuaibi, Aini Palizhati, Siddharth Goyal, Aditya Grover, Adeesh Kolluru, Janice Lan, Ammar Rizvi, Anuroop Sriram, Brandon M. Wood, Devi Parikh, Zachary W. Ulissi, C. Lawrence Zitnick, Guolin Ke, Shuxin Zheng, Yu Shi, Di He, Tie-Yan Liu, Chengxuan Ying, Jiacheng You, Yihan He, Rostislav Grigoriev, Ruslan Lukin, Adel Yarullin, Max Faleev
2021	A*	`conf`	Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons. ICML Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang
2021	J	`jnl`	Towards Certifying 𝓁 CoRR Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang
2021	J	`jnl`	Transformers with Competitive Ensembles of Independent Mechanisms. CoRR Alex Lamb, Di He, Anirudh Goyal, Guolin Ke, Chien-Feng Liao, Mirco Ravanelli, Yoshua Bengio
2020	J	`jnl`	GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. CoRR Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang
2020	A*	`conf`	I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations. IJCAI Xufang Luo, Qi Meng, Di He, Wei Chen, Yunhong Wang
2020	A*	`conf`	Incorporating BERT into Neural Machine Translation. ICLR Jinhua Zhu, Yingce Xia, Lijun Wu, Di He, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu
2020	J	`jnl`	Incorporating BERT into Neural Machine Translation. CoRR Jinhua Zhu, Yingce Xia, Lijun Wu, Di He, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu
2020	—	`conf`	Invertible Image Rescaling. ECCV (1) Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu
2020	J	`jnl`	Invertible Image Rescaling. CoRR Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu
2020	A*	`conf`	MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius. ICLR Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang
2020	J	`jnl`	MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius. CoRR Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang
2020	J	`jnl`	MC-BERT: Efficient Language Pre-Training via a Meta Controller. CoRR Zhenhui Xu, Linyuan Gong, Guolin Ke, Di He, Shuxin Zheng, Liwei Wang, Jiang Bian, Tie-Yan Liu
2020	A*	`conf`	On Layer Normalization in the Transformer Architecture. ICML Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu
2020	J	`jnl`	On Layer Normalization in the Transformer Architecture. CoRR Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu
2020	J	`jnl`	Rethinking Positional Encoding in Language Pre-training. CoRR Guolin Ke, Di He, Tie-Yan Liu
2020	J	`jnl`	Taking Notes on the Fly Helps BERT Pre-training. CoRR Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
2020	J	`jnl`	Transferred Discrepancy: Quantifying the Difference Between Representations. CoRR Yunzhen Feng, Runtian Zhai, Di He, Liwei Wang, Bin Dong
2019	J	`jnl`	A Gram-Gauss-Newton Method Learning Overparameterized Deep Neural Networks for Regression Problems. CoRR Tianle Cai, Ruiqi Gao, Jikai Hou, Siyu Chen, Dong Wang, Di He, Zhihua Zhang, Liwei Wang
2019	J	`jnl`	Adversarially Robust Generalization Just Requires More Unlabeled Data. CoRR Runtian Zhai, Tianle Cai, Di He, Chen Dan, Kun He, John E. Hopcroft, Liwei Wang
2019	J	`jnl`	Defective Convolutional Layers Learn Robust CNNs. CoRR Tiange Luo, Tianle Cai, Mengxiao Zhang, Siyu Chen, Di He, Liwei Wang
2019	A*	`conf`	Deliberation Learning for Image-to-Image Translation. IJCAI Tianyu He, Yingce Xia, Jianxin Lin, Xu Tan, Di He, Tao Qin, Zhibo Chen
2019	A*	`conf`	Efficient Training of BERT by Progressively Stacking. ICML Linyuan Gong, Di He, Zhuohan Li, Tao Qin, Liwei Wang, Tie-Yan Liu
2019	A*	`conf`	Fast Structured Decoding for Sequence Models. NeurIPS Zhiqing Sun, Zhuohan Li, Haoqing Wang, Di He, Zi Lin, Zhi-Hong Deng
2019	J	`jnl`	Fast Structured Decoding for Sequence Models. CoRR Zhiqing Sun, Zhuohan Li, Haoqing Wang, Zi Lin, Di He, Zhi-Hong Deng
2019	—	`conf`	Hint-Based Training for Non-Autoregressive Machine Translation. EMNLP/IJCNLP (1) Zhuohan Li, Zi Lin, Di He, Fei Tian, Tao Qin, Liwei Wang, Tie-Yan Liu
2019	J	`jnl`	Hint-Based Training for Non-Autoregressive Machine Translation. CoRR Zhuohan Li, Zi Lin, Di He, Fei Tian, Tao Qin, Liwei Wang, Tie-Yan Liu
2019	—	`conf`	Machine Translation With Weakly Paired Documents. EMNLP/IJCNLP (1) Lijun Wu, Jinhua Zhu, Di He, Fei Gao, Tao Qin, Jianhuang Lai, Tie-Yan Liu
2019	—	`conf`	Microsoft Research Asia's Systems for WMT19. WMT (2) Yingce Xia, Xu Tan, Fei Tian, Fei Gao, Di He, Weicong Chen, Yang Fan, Linyuan Gong, Yichong Leng, Renqian Luo, Yiren Wang, Lijun Wu, Jinhua Zhu, Tao Qin, Tie-Yan Liu
2019	—	`conf`	Multilingual Neural Machine Translation with Knowledge Distillation. ICLR (Poster) Xu Tan, Yi Ren, Di He, Tao Qin, Zhou Zhao, Tie-Yan Liu
2019	J	`jnl`	Multilingual Neural Machine Translation with Knowledge Distillation. CoRR Xu Tan, Yi Ren, Di He, Tao Qin, Zhou Zhao, Tie-Yan Liu
2019	—	`conf`	Multilingual Neural Machine Translation with Language Clustering. EMNLP/IJCNLP (1) Xu Tan, Jiale Chen, Di He, Yingce Xia, Tao Qin, Tie-Yan Liu
2019	J	`jnl`	Multilingual Neural Machine Translation with Language Clustering. CoRR Xu Tan, Jiale Chen, Di He, Yingce Xia, Tao Qin, Tie-Yan Liu
2019	A*	`conf`	Non-Autoregressive Machine Translation with Auxiliary Regularization. AAAI Yiren Wang, Fei Tian, Di He, Tao Qin, ChengXiang Zhai, Tie-Yan Liu
2019	J	`jnl`	Non-Autoregressive Machine Translation with Auxiliary Regularization. CoRR Yiren Wang, Fei Tian, Di He, Tao Qin, ChengXiang Zhai, Tie-Yan Liu
2019	A*	`conf`	Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input. AAAI Junliang Guo, Xu Tan, Di He, Tao Qin, Linli Xu, Tie-Yan Liu
2019	J	`jnl`	On the Anomalous Generalization of GANs. CoRR Jinchen Xuan, Yunchang Yang, Ze Yang, Di He, Liwei Wang
2019	—	`conf`	Representation Degeneration Problem in Training Natural Language Generation Models. ICLR (Poster) Jun Gao, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu
2019	J	`jnl`	Representation Degeneration Problem in Training Natural Language Generation Models. CoRR Jun Gao, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu
2019	A*	`conf`	Sentence-Wise Smooth Regularization for Sequence to Sequence Learning. AAAI Chengyue Gong, Xu Tan, Di He, Tao Qin
2019	A*	`conf`	Tied Transformers: Neural Machine Translation with Shared Encoder and Decoder. AAAI Yingce Xia, Tianyu He, Xu Tan, Fei Tian, Di He, Tao Qin
2019	A*	`conf`	Towards a Deep and Unified Understanding of Deep Neural Models in NLP. ICML Chaoyu Guan, Xiting Wang, Quanshi Zhang, Runjin Chen, Di He, Xing Xie
2019	J	`jnl`	Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View. CoRR Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun, Bin Dong, Tao Qin, Liwei Wang, Tie-Yan Liu
2018	A*	`conf`	Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter. EMNLP Lijun Wu, Xu Tan, Di He, Fei Tian, Tao Qin, Jianhuang Lai, Tie-Yan Liu
2018	J	`jnl`	Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter. CoRR Lijun Wu, Xu Tan, Di He, Fei Tian, Tao Qin, Jianhuang Lai, Tie-Yan Liu
2018	—	`conf`	Dense Information Flow for Neural Machine Translation. NAACL-HLT Yanyao Shen, Xu Tan, Di He, Tao Qin, Tie-Yan Liu
2018	J	`jnl`	Dense Information Flow for Neural Machine Translation. CoRR Yanyao Shen, Xu Tan, Di He, Tao Qin, Tie-Yan Liu
2018	B	`conf`	Double Path Networks for Sequence to Sequence Learning. COLING Kaitao Song, Xu Tan, Di He, Jianfeng Lu, Tao Qin, Tie-Yan Liu
2018	J	`jnl`	Double Path Networks for Sequence to Sequence Learning. CoRR Kaitao Song, Xu Tan, Di He, Jianfeng Lu, Tao Qin, Tie-Yan Liu
2018	A*	`conf`	FRAGE: Frequency-Agnostic Word Representation. NeurIPS Chengyue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu
2018	J	`jnl`	FRAGE: Frequency-Agnostic Word Representation. CoRR Chengyue Gong, Di He, Xu Tan, Tao Qin, Liwei Wang, Tie-Yan Liu
2018	A*	`conf`	Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation. NeurIPS Tianyu He, Xu Tan, Yingce Xia, Di He, Tao Qin, Zhibo Chen, Tie-Yan Liu
2018	J	`jnl`	Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input. CoRR Junliang Guo, Xu Tan, Di He, Tao Qin, Linli Xu, Tie-Yan Liu
2018	J	`jnl`	Sentence-wise Smooth Regularization for Sequence to Sequence Learning. CoRR Chengyue Gong, Xu Tan, Di He, Tao Qin
2018	A*	`conf`	Towards Binary-Valued Gates for Robust LSTM Training. ICML Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tie-Yan Liu
2018	J	`jnl`	Towards Binary-Valued Gates for Robust LSTM Training. CoRR Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tie-Yan Liu
2017	—	`conf`	Decoding with Value Networks for Neural Machine Translation. NIPS Di He, Hanqing Lu, Yingce Xia, Tao Qin, Liwei Wang, Tie-Yan Liu
2017	—	`conf`	Scale Effects in Web Search. WINE Di He, Aadharsh Kannan, Tie-Yan Liu, R. Preston McAfee, Tao Qin, Justin M. Rao
2016	—	`conf`	Dual Learning for Machine Translation. NIPS Di He, Yingce Xia, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, Wei-Ying Ma
2016	J	`jnl`	Dual Learning for Machine Translation. CoRR Yingce Xia, Di He, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, Wei-Ying Ma
2016	J	`jnl`	Sentence Level Recurrent Topic Model: Letting Topics Speak for Themselves. CoRR Fei Tian, Bin Gao, Di He, Tie-Yan Liu
2014	J	`jnl`	A Game-theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search. CoRR Di He, Wei Chen, Liwei Wang, Tie-Yan Liu
2014	J	`jnl`	Generalized Second Price Auction with Probabilistic Broad Match. CoRR Wei Chen, Di He, Tie-Yan Liu, Tao Qin, Yixin Tao, Liwei Wang
2014	A*	`conf`	Generalized second price auction with probabilistic broad match. EC Wei Chen, Di He, Tie-Yan Liu, Tao Qin, Yixin Tao, Liwei Wang
2013	A*	`conf`	A Game-Theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search. IJCAI Di He, Wei Chen, Liwei Wang, Tie-Yan Liu
2013	J	`jnl`	A Theoretical Analysis of NDCG Type Ranking Measures CoRR Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Tie-Yan Liu, Wei Chen
2013	A*	`conf`	A Theoretical Analysis of NDCG Type Ranking Measures. COLT Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Tie-Yan Liu
2013	J	`jnl`	Online learning for auction mechanism in bandit setting. Decis. Support Syst. Di He, Wei Chen, Liwei Wang, Tie-Yan Liu