Ranking Measures and Loss Functions in Learning to Rank. - Wei Chen 034; Tie-Yan Liu; Yanyan Lan; Zhiming Ma; Hang Li 001 (NIPS, 2009)

Two-Layer Generalization Analysis for Ranking Using Rademacher Average. - Wei Chen 034; Tie-Yan Liu; Zhiming Ma (NIPS, 2010)

Convergence Analysis for Weighted Joint Strategy Fictitious Play in Generalized Second Price Auction. - Lei Yao; Wei Chen 034; Tie-Yan Liu (WINE, 2012)

A Game-Theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search. - Di He 001; Wei Chen 034; Liwei Wang 001; Tie-Yan Liu (IJCAI, 2013)

A Theoretical Analysis of NDCG Type Ranking Measures - Yining Wang 001; Liwei Wang 001; Yuanzhi Li; Di He 001; Tie-Yan Liu; Wei Chen 034 (CoRR, 2013)

Online learning for auction mechanism in bandit setting. - Di He 001; Wei Chen 034; Liwei Wang 001; Tie-Yan Liu (Decis. Support Syst., 2013)

Agent Behavior Prediction and Its Generalization Analysis. - Fei Tian; Haifang Li 002; Wei Chen 034; Tao Qin 001; Enhong Chen; Tie-Yan Liu (AAAI, 2014)

Generalized second price auction with probabilistic broad match. - Wei Chen 034; Di He 001; Tie-Yan Liu; Tao Qin 001; Yixin Tao; Liwei Wang 001 (EC, 2014)

Sampling dilemma: towards effective data sampling for click prediction in sponsored search. - Jun Feng; Jiang Bian 002; Taifeng Wang; Wei Chen 034; Xiaoyan Zhu 001; Tie-Yan Liu (WSDM, 2014)

Generalization Analysis for Game-Theoretic Machine Learning. - Haifang Li 002; Fei Tian; Wei Chen 034; Tao Qin 001; Tie-Yan Liu (CoRR, 2014)

Sponsored Search Auctions: Recent Advances and Future Directions. - Tao Qin 001; Wei Chen 034; Tie-Yan Liu (ACM Trans. Intell. Syst. Technol., 2014)

Generalization Analysis for Game-Theoretic Machine Learning. - Haifang Li 002; Fei Tian; Wei Chen 034; Tao Qin 001; Zhiming Ma; Tie-Yan Liu (AAAI, 2015)

Mechanism Learning with Mechanism Induced Data. - Tie-Yan Liu; Wei Chen 034; Tao Qin 001 (AAAI, 2015)

Large Margin Deep Neural Networks: Theory and Algorithms. - Shizhao Sun; Wei Chen 034; Liwei Wang 001; Tie-Yan Liu (CoRR, 2015)

On the Depth of Deep Neural Networks: A Theoretical View. - Shizhao Sun; Wei Chen 034; Liwei Wang 001; Xiaoguang Liu 001; Tie-Yan Liu (AAAI, 2016)

Asynchronous Accelerated Stochastic Gradient Descent. - Qi Meng; Wei Chen 034; Jingcheng Yu; Taifeng Wang; Zhiming Ma; Tie-Yan Liu (IJCAI, 2016)

A Communication-Efficient Parallel Algorithm for Decision Tree. - Qi Meng; Guolin Ke; Taifeng Wang; Wei Chen 034; Qiwei Ye; Zhiming Ma; Tie-Yan Liu (NIPS, 2016)

Asynchronous Stochastic Gradient Descent with Delay Compensation for Distributed Deep Learning. - Shuxin Zheng; Qi Meng; Taifeng Wang; Wei Chen 034; Nenghai Yu; Zhiming Ma; Tie-Yan Liu (CoRR, 2016)

Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction. - Qi Meng; Wei Chen 034; Jingcheng Yu; Taifeng Wang; Zhiming Ma; Tie-Yan Liu (AAAI, 2017)

Generalization Error Bounds for Optimization Algorithms via Stability. - Qi Meng; Yue Wang 017; Wei Chen 034; Taifeng Wang; Zhiming Ma; Tie-Yan Liu (AAAI, 2017)

Dynamic Group Behavior Analysis and Its Application in Network Abnormal Behavior Detection. - Yan Tong; Jian Zhang; Wei Chen 034; Mingdi Xu; Tao Qin 001 (ChinaCom (2), 2017)

Dual Supervised Learning. - Yingce Xia; Tao Qin 001; Wei Chen 034; Jiang Bian 002; Nenghai Yu; Tie-Yan Liu (ICML, 2017)

Asynchronous Stochastic Gradient Descent with Delay Compensation. - Shuxin Zheng; Qi Meng; Taifeng Wang; Wei Chen 034; Nenghai Yu; Zhiming Ma; Tie-Yan Liu (ICML, 2017)

Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems. - Quanming Yao; James T. Kwok; Fei Gao 018; Wei Chen 034; Tie-Yan Liu (IJCAI, 2017)

LightGBM: A Highly Efficient Gradient Boosting Decision Tree. - Guolin Ke; Qi Meng; Thomas Finley; Taifeng Wang; Wei Chen 034; Weidong Ma; Qiwei Ye; Tie-Yan Liu (NIPS, 2017)

Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov Setting. - Yue Wang 017; Wei Chen 034; Yuting Liu 002; Zhiming Ma; Tie-Yan Liu (NIPS, 2017)

Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks. - Shizhao Sun; Wei Chen 034; Jiang Bian 002; Xiaoguang Liu 001; Tie-Yan Liu (ECML/PKDD (1), 2017)

Distributed Machine Learning: Foundations, Trends, and Practices. - Tie-Yan Liu; Wei Chen 034; Taifeng Wang (WWW (Companion Volume), 2017)

Slim-DP: A Light Communication Data Parallelism for DNN. - Shizhao Sun; Wei Chen 034; Jiang Bian 002; Xiaoguang Liu 001; Tie-Yan Liu (CoRR, 2017)

Slim-DP: A Multi-Agent System for Communication-Efficient Distributed Deep Learning. - Shizhao Sun; Wei Chen 034; Jiang Bian 002; Xiaoguang Liu 001; Tie-Yan Liu (AAMAS, 2018)

Towards Binary-Valued Gates for Robust LSTM Training. - Zhuohan Li 001; Di He 001; Fei Tian; Wei Chen 034; Tao Qin 001; Liwei Wang 001; Tie-Yan Liu (ICML, 2018)

Differential Equations for Modeling Asynchronous Algorithms. - Li He; Qi Meng; Wei Chen 034; Zhiming Ma; Tie-Yan Liu (IJCAI, 2018)

On the Local Hessian in Back-propagation. - Huishuai Zhang; Wei Chen 034; Tie-Yan Liu (NeurIPS, 2018)

Optimizing Neural Networks in the Equivalent Class Space. - Qi Meng; Wei Chen 034; Shuxin Zheng; Qiwei Ye; Tie-Yan Liu (CoRR, 2018)

Train Feedfoward Neural Network with Layer-wise Adaptive Rate via Approximating Back-matching Propagation. - Huishuai Zhang; Wei Chen 034; Tie-Yan Liu (CoRR, 2018)

Target Transfer Q-Learning and Its Convergence Analysis. - Yue Wang 017; Qi Meng; Wei Chen 034; Yuting Liu 002; Zhiming Ma; Tie-Yan Liu (CoRR, 2018)

基于BiLSTM-CRF的关键词自动抽取 (Automatic Keyword Extraction Based on BiLSTM-CRF). - Wei Chen 034; Youzheng Wu; Wenliang Chen; Min Zhang 005 (计算机科学, 2018)

Capacity Control of ReLU Neural Networks by Basis-Path Norm. - Shuxin Zheng; Qi Meng; Huishuai Zhang; Wei Chen 034; Nenghai Yu; Tie-Yan Liu (AAAI, 2019)

G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space. - Qi Meng; Shuxin Zheng; Huishuai Zhang; Wei Chen 034; Qiwei Ye; Zhi-Ming Ma; Nenghai Yu; Tie-Yan Liu (ICLR (Poster), 2019)

BN-invariant Sharpness Regularizes the Training Model to Better Generalization. - Mingyang Yi; Huishuai Zhang; Wei Chen 034; Zhi-Ming Ma; Tie-Yan Liu (IJCAI, 2019)

Positively Scale-Invariant Flatness of ReLU Neural Networks. - Mingyang Yi; Qi Meng; Wei Chen 034; Zhi-Ming Ma; Tie-Yan Liu (CoRR, 2019)

Reinforcement Learning with Dynamic Boltzmann Softmax Updates. - Ling Pan; Qingpeng Cai 001; Qi Meng; Wei Chen 034; Longbo Huang; Tie-Yan Liu (CoRR, 2019)

Training Over-parameterized Deep ResNet Is almost as Easy as Training a Two-layer Network. - Huishuai Zhang; Da Yu; Wei Chen 034; Tie-Yan Liu (CoRR, 2019)

OptQuant: Distributed training of neural networks with optimized quantization mechanisms. - Li He; Shuxin Zheng; Wei Chen 034; Zhiming Ma; Tie-Yan Liu (Neurocomputing, 2019)

Convergence analysis of distributed stochastic gradient descent with shuffling. - Qi Meng; Wei Chen 034; Yue Wang 017; Zhi-Ming Ma; Tie-Yan Liu (Neurocomputing, 2019)

Combinatorial Pure Exploration for Dueling Bandit. - Wei Chen 034; Yihan Du; Longbo Huang; Haoyu Zhao (ICML, 2020)

(Locally) Differentially Private Combinatorial Semi-Bandits. - Xiaoyu Chen 008; Kai Zheng 007; Zixin Zhou; Yunchang Yang; Wei Chen 034; Liwei Wang 001 (ICML, 2020)

I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations. - Xufang Luo; Qi Meng; Di He 001; Wei Chen 034; Yunhong Wang 001 (IJCAI, 2020)

Reinforcement Learning with Dynamic Boltzmann Softmax Updates. - Ling Pan; Qingpeng Cai 001; Qi Meng; Wei Chen 034; Longbo Huang (IJCAI, 2020)

Gradient Perturbation is Underrated for Differentially Private Convex Optimization. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (IJCAI, 2020)

Combinatorial Semi-Bandit in the Non-Stationary Environment. - Wei Chen 034; Liwei Wang 001; Haoyu Zhao; Kai Zheng 007 (CoRR, 2020)

Combinatorial Pure Exploration with Partial or Full-Bandit Linear Feedback. - Wei Chen 034; Yihan Du; Yuko Kuroki (CoRR, 2020)

Dynamic of Stochastic Gradient Descent with State-Dependent Noise. - Qi Meng; Shiqi Gong; Wei Chen 034; Zhi-Ming Ma; Tie-Yan Liu (CoRR, 2020)

Membership Inference with Privately Augmented Data Endorses the Benign while Suppresses the Adversary. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (CoRR, 2020)

Learning Causal Semantic Representation for Out-of-Distribution Prediction. - Chang Liu 030; Xinwei Sun 001; Jindong Wang 001; Tao Li 040; Tao Qin 001; Wei Chen 034; Tie-Yan Liu (CoRR, 2020)

Latent Causal Invariant Model. - Xinwei Sun 001; Botong Wu; Chang Liu 030; Xiangyu Zheng; Wei Chen 034; Tao Qin 001; Tie-Yan Liu (CoRR, 2020)

Identifying Invariant Texture Violation for Robust Deepfake Detection. - Xinwei Sun 001; Botong Wu; Wei Chen 034 (CoRR, 2020)

Target transfer Q-learning and its convergence analysis. - Yue Wang 017; Yuting Liu 002; Wei Chen 034; Zhi-Ming Ma; Tie-Yan Liu (Neurocomputing, 2020)

Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data. - Shicong Cen; Huishuai Zhang; Yuejie Chi; Wei Chen 034; Tie-Yan Liu (IEEE Trans. Signal Process., 2020)

Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback. - Yihan Du; Yuko Kuroki; Wei Chen 034 (AAAI, 2021)

How Does Data Augmentation Affect Privacy in Machine Learning? - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (AAAI, 2021)

EARL: Informative Knowledge-Grounded Conversation Generation with Entity-Agnostic Representation Learning. - Hao Zhou 012; Minlie Huang; Yong Liu; Wei Chen 034; Xiaoyan Zhu 001 (EMNLP (1), 2021)

Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. - Da Yu; Huishuai Zhang; Wei Chen 034; Tie-Yan Liu (ICLR, 2021)

The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks. - Bohan Wang; Qi Meng; Wei Chen 034; Tie-Yan Liu (ICML, 2021)

Large Scale Private Learning via Low-rank Reparametrization. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (ICML, 2021)

R-Drop: Regularized Dropout for Neural Networks. - Xiaobo Liang; Lijun Wu 003; Juntao Li; Yue Wang 039; Qi Meng; Tao Qin 001; Wei Chen 034; Min Zhang 005; Tie-Yan Liu (NeurIPS, 2021)

Learning Causal Semantic Representation for Out-of-Distribution Prediction. - Chang Liu 030; Xinwei Sun 001; Jindong Wang 001; Haoyue Tang; Tao Li 040; Tao Qin 001; Wei Chen 034; Tie-Yan Liu (NeurIPS, 2021)

Recovering Latent Causal Factor for Generalization to Distributional Shifts. - Xinwei Sun 001; Botong Wu; Xiangyu Zheng; Chang Liu 030; Wei Chen 034; Tao Qin 001; Tie-Yan Liu (NeurIPS, 2021)

Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD. - Bohan Wang; Huishuai Zhang; Jieyu Zhang; Qi Meng; Wei Chen 034; Tie-Yan Liu (NeurIPS, 2021)

Path-BN: Towards effective batch normalization in the Path Space for ReLU networks. - Xufang Luo; Qi Meng; Wei Chen 034; Yunhong Wang 001; Tie-Yan Liu (UAI, 2021)

Towards Accelerating Training of Batch Normalization: A Manifold Perspective. - Mingyang Yi; Qi Meng; Wei Chen 034; Zhi-Ming Ma (CoRR, 2021)

Combinatorial Pure Exploration with Bottleneck Reward Function and its Extension to General Reward Functions. - Yihan Du; Yuko Kuroki; Wei Chen 034 (CoRR, 2021)

Adversarial Training with Rectified Rejection. - Tianyu Pang; Huishuai Zhang; Di He 001; Yinpeng Dong; Hang Su 006; Wei Chen 034; Jun Zhu 001; Tie-Yan Liu (CoRR, 2021)

Machine-Learning Non-Conservative Dynamics for New-Physics Detection. - Ziming Liu; Bohan Wang; Qi Meng; Wei Chen 034; Max Tegmark; Tie-Yan Liu (CoRR, 2021)

PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Driven Adaptive Prior. - Sang-gil Lee; Heeseung Kim; Chaehun Shin; Xu Tan 003; Chang Liu 030; Qi Meng; Tao Qin 001; Wei Chen 034; Sungroh Yoon; Tie-Yan Liu (CoRR, 2021)

Regularized OFU: an Efficient UCB Estimator forNon-linear Contextual Bandit. - Yichi Zhou; Shihong Song; Huishuai Zhang; Jun Zhu 001; Wei Chen 034; Tie-Yan Liu (CoRR, 2021)

Causally Invariant Predictor with Shift-Robustness. - Xiangyu Zheng; Xinwei Sun 001; Wei Chen 034; Tie-Yan Liu (CoRR, 2021)

Momentum Doesn't Change the Implicit Bias. - Bohan Wang; Qi Meng; Huishuai Zhang; Ruoyu Sun 001; Wei Chen 034; Zhi-Ming Ma (CoRR, 2021)

Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD. - Bohan Wang; Huishuai Zhang; Jieyu Zhang; Qi Meng; Wei Chen 034; Tie-Yan Liu (CoRR, 2021)

Equivariant vector field network for many-body system modeling. - Weitao Du; He Zhang; Yuanqi Du; Qi Meng; Wei Chen 034; Bin Shao; Tie-Yan Liu (CoRR, 2021)

Indiscriminate Poisoning Attacks Are Shortcuts. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (CoRR, 2021)

Interpreting the Basis Path Set in Neural Networks. - Juanping Zhu; Qi Meng; Wei Chen 034; Zhiming Ma (J. Syst. Sci. Complex., 2021)

Certified Robustness to Word Substitution Ranking Attack for Neural Ranking Models. - Chen Wu; Ruqing Zhang 001; Jiafeng Guo; Wei Chen 034; Yixing Fan; Maarten de Rijke; Xueqi Cheng (CIKM, 2022)

Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart. - Tianyu Pang; Huishuai Zhang; Di He 001; Yinpeng Dong; Hang Su 006; Wei Chen 034; Jun Zhu 001; Tie-Yan Liu (CVPR, 2022)

PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior. - Sang-gil Lee; Heeseung Kim; Chaehun Shin; Xu Tan 003; Chang Liu 030; Qi Meng; Tao Qin 001; Wei Chen 034; Sungroh Yoon; Tie-Yan Liu (ICLR, 2022)

Gradient Information Matters in Policy Optimization by Back-propagating through Model. - Chongchong Li; Yue Wang 017; Wei Chen 034; Yuting Liu 002; Zhi-Ming Ma; Tie-Yan Liu (ICLR, 2022)

SE(3) Equivariant Graph Neural Networks with Complete Local Frames. - Weitao Du; He Zhang; Yuanqi Du; Qi Meng; Wei Chen 034; Nanning Zheng 001; Bin Shao; Tie-Yan Liu (ICML, 2022)

Availability Attacks Create Shortcuts. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (KDD, 2022)

Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. - Jiawei Huang; Li Zhao 007; Tao Qin 001; Wei Chen 034; Nan Jiang 008; Tie-Yan Liu (NeurIPS, 2022)

Does Momentum Change the Implicit Regularization on Separable Data? - Bohan Wang; Qi Meng; Huishuai Zhang; Ruoyu Sun 001; Wei Chen 034; Zhi-Ming Ma; Tie-Yan Liu (NeurIPS, 2022)

Branching Reinforcement Learning. - Yihan Du; Wei Chen 034 (CoRR, 2022)

Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs. - Peiyan Hu; Qi Meng; Bingguang Chen; Shiqi Gong; Yue Wang 017; Wei Chen 034; Rongchan Zhu; Zhi-Ming Ma; Tie-Yan Liu (CoRR, 2022)

Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization. - Xiaodong Yang; Huishuai Zhang; Wei Chen 034; Tie-Yan Liu (CoRR, 2022)

Provable Adaptivity in Adam. - Bohan Wang; Yushun Zhang; Huishuai Zhang; Qi Meng; Zhi-Ming Ma; Tie-Yan Liu; Wei Chen 034 (CoRR, 2022)

Constructing the Basis Path Set by Eliminating the Path Dependency. - Juanping Zhu; Qi Meng; Wei Chen 034; Yue Wang 017; Zhiming Ma (J. Syst. Sci. Complex., 2022)

Stabilize deep ResNet with a sharp scaling factor τ. - Huishuai Zhang; Da Yu; Mingyang Yi; Wei Chen 034; Tie-Yan Liu (Mach. Learn., 2022)

L2R: Lifelong Learning for First-stage Retrieval with Backward-Compatible Representations. - Yinqiong Cai; Keping Bi; Yixing Fan; Jiafeng Guo; Wei Chen 034; Xueqi Cheng (CIKM, 2023)

Continual Learning for Generative Retrieval over Dynamic Corpora. - Jiangui Chen; Ruqing Zhang 001; Jiafeng Guo; Maarten de Rijke; Wei Chen 034; Yixing Fan; Xueqi Cheng (CIKM, 2023)

Inducing Causal Structure for Abstractive Text Summarization. - Lu Chen; Ruqing Zhang 001; Wei Huang; Wei Chen 034; Jiafeng Guo; Xueqi Cheng (CIKM, 2023)

Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method. - Yu-An Liu 028; Ruqing Zhang 001; Jiafeng Guo; Maarten de Rijke; Wei Chen 034; Yixing Fan; Xueqi Cheng (CIKM, 2023)

Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions. - Bohan Wang; Huishuai Zhang; Zhiming Ma; Wei Chen 034 (COLT, 2023)

Collaborative Pure Exploration in Kernel Bandit. - Yihan Du; Wei Chen 034; Yuko Kuroki; Longbo Huang (ICLR, 2023)

Closing the gap between the upper bound and lower bound of Adam's iteration complexity. - Bohan Wang; Jingwen Fu; Huishuai Zhang; Nanning Zheng 001; Wei Chen 034 (NeurIPS, 2023)

Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models. - Yu-An Liu 028; Ruqing Zhang 001; Jiafeng Guo; Maarten de Rijke; Wei Chen 034; Yixing Fan; Xueqi Cheng (SIGIR, 2023)

When and Why Momentum Accelerates SGD: An Empirical Study. - Jingwen Fu; Bohan Wang; Huishuai Zhang; Zhizheng Zhang 004; Wei Chen 034; Nanning Zheng 001 (CoRR, 2023)

Power-law Dynamic arising from machine learning. - Wei Chen 034; Weitao Du; Zhi-Ming Ma; Qi Meng (CoRR, 2023)

On the Robustness of Generative Retrieval Models: An Out-of-Distribution Perspective. - Yu-An Liu 028; Ruqing Zhang 001; Jiafeng Guo; Wei Chen 034; Xueqi Cheng (CoRR, 2023)

L^2R: Lifelong Learning for First-stage Retrieval with Backward-Compatible Representations. - Yinqiong Cai; Keping Bi; Yixing Fan; Jiafeng Guo; Wei Chen 034; Xueqi Cheng (CoRR, 2023)

Incorporating NODE with pre-trained neural differential operator for learning dynamics. - Shiqi Gong; Qi Meng; Yue Wang 017; Lijun Wu 003; Wei Chen 034; Zhiming Ma; Tie-Yan Liu (Neurocomputing, 2023)

Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off. - Yu-An Liu 028; Ruqing Zhang 001; Mingkun Zhang; Wei Chen 034; Maarten de Rijke; Jiafeng Guo; Xueqi Cheng (AAAI, 2024)

Classifier Guidance Enhances Diffusion-Based Adversarial Purification by Preserving Predictive Information. - Mingkun Zhang; Jianing Li; Wei Chen 034; Jiafeng Guo; Xueqi Cheng (ECAI, 2024)

Provable Adaptivity of Adam under Non-uniform Smoothness. - Bohan Wang; Yushun Zhang; Huishuai Zhang; Qi Meng; Ruoyu Sun 001; Zhi-Ming Ma; Tie-Yan Liu; Zhi-Quan Luo; Wei Chen 034 (KDD, 2024)

Generative Retrieval Meets Multi-Graded Relevance. - Yubao Tang; Ruqing Zhang 001; Jiafeng Guo; Maarten de Rijke; Wei Chen 034; Xueqi Cheng (NeurIPS, 2024)

CausalDiff: Causality-Inspired Disentanglement via Diffusion Model for Adversarial Defense. - Mingkun Zhang; Keping Bi; Wei Chen 034; Quanrun Chen; Jiafeng Guo; Xueqi Cheng (NeurIPS, 2024)

A Unified Causal View of Instruction Tuning. - Lu Chen; Wei Huang; Ruqing Zhang 001; Wei Chen 034; Jiafeng Guo; Xueqi Cheng (CoRR, 2024)

On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond. - Bohan Wang; Huishuai Zhang; Qi Meng; Ruoyu Sun 001; Zhi-Ming Ma; Wei Chen 034 (CoRR, 2024)

Listwise Generative Retrieval Models via a Sequential Learning Process. - Yubao Tang; Ruqing Zhang 001; Jiafeng Guo; Maarten de Rijke; Wei Chen 034; Xueqi Cheng (ACM Trans. Inf. Syst., 2024)

Evaluating Implicit Bias in Large Language Models by Attacking From a Psychometric Perspective. - Yuchen Wen; Keping Bi; Wei Chen 034; Jiafeng Guo; Xueqi Cheng (ACL (Findings), 2025)

CLIPure: Purification in Latent Space via CLIP for Adversarially Robust Zero-Shot Classification. - Mingkun Zhang; Keping Bi; Wei Chen 034; Jiafeng Guo; Xueqi Cheng (ICLR, 2025)

Continuous K-Max Bandits. - Yu Chen 074; Siwei Wang 002; Longbo Huang; Wei Chen 034 (CoRR, 2025)

CAME: Competitively Learning a Mixture-of-Experts Model for First-stage Retrieval. - Jiafeng Guo; Yinqiong Cai; Keping Bi; Yixing Fan; Wei Chen 034; Ruqing Zhang 001; Xueqi Cheng (ACM Trans. Inf. Syst., 2025)