Wang, Yifei

82 publications

TMLR 2026 StructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs Jialin Yang, Dongfu Jiang, Tony He, Sherman Siu, Yuxuan Zhang, Disen Liao, Zhuofeng Li, Huaye Zeng, Yiming Jia, Haozhe Wang, Benjamin Schneider, Chi Ruan, Wentao Ma, Zhiheng Lyu, Yifei Wang, Yi Lu, Quy Duc Do, Ziyan Jiang, Ping Nie, Wenhu Chen

NeurIPS 2025 $\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning Xiaojun Guo, Ang Li, Yifei Wang, Stefanie Jegelka, Yisen Wang

NeurIPS 2025 A Signed Graph Approach to Understanding and Mitigating Oversmoothing Jiaqi Wang, Xinyi Wu, James Cheng, Yifei Wang

JMLR 2025 An Augmentation Overlap Theory of Contrastive Learning Qi Zhang, Yifei Wang, Yisen Wang

ICLR 2025 Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness Qi Zhang, Yifei Wang, Jingyi Cui, Xiang Pan, Qi Lei, Stefanie Jegelka, Yisen Wang

ICML 2025 Beyond Matryoshka: Revisiting Sparse Coding for Adaptive Representation Tiansheng Wen, Yifei Wang, Zequn Zeng, Zhong Peng, Yudi Su, Xinyang Liu, Bo Chen, Hongwei Liu, Stefanie Jegelka, Chenyu You

ICLR 2025 Can In-Context Learning Really Generalize to Out-of-Distribution Tasks? Qixun Wang, Yifei Wang, Xianghua Ying, Yisen Wang

NeurIPS 2025 Language Ranker: A Lightweight Ranking Framework for LLM Decoding Chenheng Zhang, Tianqi Du, Jizhe Zhang, Mingqing Xiao, Yifei Wang, Yisen Wang, Zhouchen Lin

ICML 2025 Long-Short Alignment for Effective Long-Context Modeling in LLMs Tianqi Du, Haotian Huang, Yifei Wang, Yisen Wang

NeurIPS 2025 Next Semantic Scale Prediction via Hierarchical Diffusion Language Models Cai Zhou, Chenyu Wang, Dinghuai Zhang, Shangyuan Tong, Yifei Wang, Stephen Bates, Tommi Jaakkola

ICML 2025 On the Emergence of Position Bias in Transformers Xinyi Wu, Yifei Wang, Stefanie Jegelka, Ali Jadbabaie

ICLRW 2025 On the Emergence of Position Bias in Transformers Xinyi Wu, Yifei Wang, Stefanie Jegelka, Ali Jadbabaie

ICLR 2025 Projection Head Is Secretly an Information Bottleneck Zhuo Ouyang, Kaiwen Hu, Qi Zhang, Yifei Wang, Yisen Wang

ICLR 2025 Rethinking Invariance in In-Context Learning Lizhe Fang, Yifei Wang, Khashayar Gatmiry, Lei Fang, Yisen Wang

ICLR 2025 Scaling Large Language Model-Based Multi-Agent Collaboration Chen Qian, Zihao Xie, YiFei Wang, Wei Liu, Kunlun Zhu, Hanchen Xia, Yufan Dang, Zhuoyun Du, Weize Chen, Cheng Yang, Zhiyuan Liu, Maosong Sun

AAAI 2025 Semi-IIN: Semi-Supervised Intra-Inter Modal Interaction Learning Network for Multimodal Sentiment Analysis Jinhao Lin, Yifei Wang, Yanwu Xu, Qi Liu

NeurIPS 2025 Uni-Instruct: One-Step Diffusion Model Through Unified Diffusion Divergence Instruction Yifei Wang, Weimin Bai, Colin Zhang, Debing Zhang, Weijian Luo, He Sun

ICLR 2025 What Is Wrong with Perplexity for Long-Context Language Modeling? Lizhe Fang, Yifei Wang, Zhaoyang Liu, Chenheng Zhang, Stefanie Jegelka, Jinyang Gao, Bolin Ding, Yisen Wang

ICLRW 2025 When More Is Less: Understanding Chain-of-Thought Length in LLMs Yuyang Wu, Yifei Wang, Tianqi Du, Stefanie Jegelka, Yisen Wang

NeurIPS 2024 A Canonicalization Perspective on Invariant and Equivariant Learning George Ma, Yifei Wang, Derek Lim, Stefanie Jegelka, Yisen Wang

NeurIPS 2024 A Theoretical Understanding of Self-Correction Through In-Context Alignment Yifei Wang, Yuyang Wu, Zeming Wei, Stefanie Jegelka, Yisen Wang

ICMLW 2024 A Theoretical Understanding of Self-Correction Through In-Context Alignment Yifei Wang, Yuyang Wu, Zeming Wei, Stefanie Jegelka, Yisen Wang

ICMLW 2024 A Theoretical Understanding of Self-Correction Through In-Context Alignment Yifei Wang, Yuyang Wu, Zeming Wei, Stefanie Jegelka, Yisen Wang

NeurIPS 2024 An Expectation-Maximization Algorithm for Training Clean Diffusion Models from Corrupted Observations Weimin Bai, Yifei Wang, Wenzheng Chen, He Sun

NeurIPS 2024 Autonomous Agents for Collaborative Task Under Information Asymmetry Wei Liu, Chenxi Wang, Yifei Wang, Zihao Xie, Rennai Qiu, Yufan Dang, Zhuoyun Du, Weize Chen, Cheng Yang, Chen Qian

NeurIPS 2024 Dissecting the Failure of Invariant Learning on Graphs Qixun Wang, Yifei Wang, Yisen Wang, Xianghua Ying

ICLR 2024 Do Generated Data Always Help Contrastive Learning? Yifei Wang, Jizhe Zhang, Yisen Wang

ACML 2024 Graph Neural Networks (with Proper Weights) Can Escape Oversmoothing Zhijian Zhuo, Yifei Wang, Jinwen Ma, Yisen Wang

ICLRW 2024 How to Craft Backdoors with Unlabeled Data Alone? Yifei Wang, Wenhan Ma, Stefanie Jegelka, Yisen Wang

NeurIPS 2024 In-Context Symmetries: Self-Supervised Learning Through Contextual World Models Sharut Gupta, Chenyu Wang, Yifei Wang, Tommi Jaakkola, Stefanie Jegelka

ICMLW 2024 In-Context Symmetries: Self-Supervised Learning Through Contextual World Models Sharut Gupta, Chenyu Wang, Yifei Wang, Tommi Jaakkola, Stefanie Jegelka

NeurIPSW 2024 In-Context Symmetries: Self-Supervised Learning Through Contextual World Models Sharut Gupta, Chenyu Wang, Yifei Wang, Tommi Jaakkola, Stefanie Jegelka

NeurIPSW 2024 In-Context Symmetries: Self-Supervised Learning Through Contextual World Models Sharut Gupta, Chenyu Wang, Yifei Wang, Tommi Jaakkola, Stefanie Jegelka

ICML 2024 Look Ahead or Look Around? a Theoretical Comparison Between Autoregressive and Masked Pretraining Qi Zhang, Tianqi Du, Haotian Huang, Yifei Wang, Yisen Wang

ICLR 2024 Non-Negative Contrastive Learning Yifei Wang, Qi Zhang, Yaoyu Guo, Yisen Wang

ICML 2024 OODRobustBench: A Benchmark and Large-Scale Analysis of Adversarial Robustness Under Distribution Shift Lin Li, Yifei Wang, Chawin Sitawarin, Michael W. Spratling

ICML 2024 On the Duality Between Sharpness-Aware Minimization and Adversarial Training Yihao Zhang, Hangzhou He, Jingyu Zhu, Huanran Chen, Yifei Wang, Zeming Wei

NeurIPS 2024 On the Role of Attention Masks and LayerNorm in Transformers Xinyi Wu, Amir Ajorlou, Yifei Wang, Stefanie Jegelka, Ali Jadbabaie

ICLR 2024 On the Role of Discrete Tokenization in Visual Representation Learning Tianqi Du, Yifei Wang, Yisen Wang

NeurIPSW 2024 Reasoning in Reasoning: A Hierarchical Framework for Better and Faster Neural Theorem Proving Ziyu Ye, Jiacheng Chen, Jonathan Light, Yifei Wang, Jiankai Sun, Mac Schwager, Philip Torr, Guohao Li, Yuxin Chen, Kaiyu Yang, Yisong Yue, Ziniu Hu

ICMLW 2024 Rethinking Invariance in In-Context Learning Lizhe Fang, Yifei Wang, Khashayar Gatmiry, Lei Fang, Yisen Wang

NeurIPSW 2024 The Multi-Faceted Monosemanticity in Multimodal Representations Hanqi Yan, Yulan He, Yifei Wang

NeurIPS 2024 Understanding the Role of Equivariance in Self-Supervised Learning Yifei Wang, Kaiwen Hu, Sharut Gupta, Ziyu Ye, Yisen Wang, Stefanie Jegelka

ICMLW 2024 Understanding the Role of Equivariance in Self-Supervised Learning Yifei Wang, Kaiwen Hu, Sharut Gupta, Ziyu Ye, Yisen Wang, Stefanie Jegelka

ICLRW 2024 Virtual Classifier: A Reversed Approach for Robust Image Evaluation Jizhe Zhang, Yifei Wang, Yisen Wang

ICLR 2023 A Message Passing Perspective on Learning Dynamics of Contrastive Learning Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin, Yisen Wang

NeurIPS 2023 Adversarial Examples Are Not Real Features Ang Li, Yifei Wang, Yiwen Guo, Yisen Wang

NeurIPS 2023 Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning Xiaojun Guo, Yifei Wang, Zeming Wei, Yisen Wang

NeurIPS 2023 Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective Yifei Wang, Liangchen Li, Jiansheng Yang, Zhouchen Lin, Yisen Wang

CVPR 2023 CFA: Class-Wise Calibrated Fair Adversarial Training Zeming Wei, Yifei Wang, Yiwen Guo, Yisen Wang

ICLR 2023 ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond Xiaojun Guo, Yifei Wang, Tianqi Du, Yisen Wang

IJCAI 2023 Contrastive Label Enhancement Yifei Wang, Yiyang Zhou, Jihua Zhu, Xinyuan Liu, Wenbiao Yan, Zhiqiang Tian

NeurIPS 2023 Identifiable Contrastive Learning with Automatic Feature Importance Discovery Qi Zhang, Yifei Wang, Yisen Wang

NeurIPS 2023 Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding George Ma, Yifei Wang, Yisen Wang

AAAI 2023 On the Connection Between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization Shiji Xin, Yifei Wang, Jingtong Su, Yisen Wang

ICML 2023 On the Generalization of Multi-Modal Contrastive Learning Qi Zhang, Yifei Wang, Yisen Wang

ICLR 2023 Parallel Deep Neural Networks Have Zero Duality Gap Yifei Wang, Tolga Ergen, Mert Pilanci

ICML 2023 Rethinking Weak Supervision in Helping Contrastive Learning Jingyi Cui, Weiran Huang, Yifei Wang, Yisen Wang

ICLR 2023 Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning Rundong Luo, Yifei Wang, Yisen Wang

ICLRW 2023 Rethinking the Necessity of Labels in Backdoor Removal Zidi Xiong, Dongxian Wu, Yifei Wang, Yisen Wang

ICLR 2023 Towards a Unified Theoretical Understanding of Non-Contrastive Learning via Rank Differential Mechanism Zhijian Zhuo, Yifei Wang, Jinwen Ma, Yisen Wang

AAAI 2023 USER: Unsupervised Structural Entropy-Based Robust Graph Neural Network Yifei Wang, Yupan Wang, Zeyu Zhang, Song Yang, Kaiqi Zhao, Jiamou Liu

ICLR 2023 Unbiased Stochastic Proximal Solver for Graph Neural Networks with Equilibrium States Mingjie Li, Yifei Wang, Yisen Wang, Zhouchen Lin

ICLRW 2023 What Contrastive Learning Learns Beyond Class-Wise Features? Xingyuming Liu, Yifei Wang, Yisen Wang

ICLR 2022 A Unified Contrastive Energy-Based Model for Understanding the Generative Ability of Adversarial Training Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin

NeurIPS 2022 Beyond the Best: Distribution Functional Estimation in Infinite-Armed Bandits Yifei Wang, Tavor Baharav, Yanjun Han, Jiantao Jiao, David Tse

ICLR 2022 Chaos Is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap Yifei Wang, Qi Zhang, Yisen Wang, Jiansheng Yang, Zhouchen Lin

ICML 2022 G$^2$CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters Mingjie Li, Xiaojun Guo, Yifei Wang, Yisen Wang, Zhouchen Lin

NeurIPS 2022 How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders Qi Zhang, Yifei Wang, Yisen Wang

NeurIPS 2022 Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors Qixun Wang, Yifei Wang, Hong Zhu, Yisen Wang

ICML 2022 Optimization-Induced Graph Implicit Nonlinear Diffusion Qi Chen, Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin

ICLR 2022 The Convex Geometry of Backpropagation: Neural Network Gradient Flows Converge to Extreme Points of the Dual Convex Program Yifei Wang, Mert Pilanci

ICLR 2022 The Hidden Convex Optimization Landscape of Regularized Two-Layer ReLU Networks: An Exact Characterization of Optimal Solutions Yifei Wang, Jonathan Lacotte, Mert Pilanci

NeurIPS 2022 When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture Yichuan Mo, Dongxian Wu, Yifei Wang, Yiwen Guo, Yisen Wang

ICML 2021 Adaptive Newton Sketch: Linear-Time Optimization with Quadratic Convergence and Effective Hessian Dimensionality Jonathan Lacotte, Yifei Wang, Mert Pilanci

ICMLW 2021 Demystifying Adversarial Training via a Unified Probabilistic Framework Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin

NeurIPS 2021 Dissecting the Diffusion Process in Linear Graph Convolutional Networks Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin

ICCV 2021 Dynamic Context-Sensitive Filtering Network for Video Salient Object Detection Miao Zhang, Jie Liu, Yifei Wang, Yongri Piao, Shunyu Yao, Wei Ji, Jingjing Li, Huchuan Lu, Zhongxuan Luo

ICLR 2021 On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections Peizhao Li, Yifei Wang, Han Zhao, Pengyu Hong, Hongfu Liu

ECML-PKDD 2021 Reparameterized Sampling for Generative Adversarial Networks Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin

NeurIPS 2021 Residual Relaxation for Multi-View Representation Learning Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang, Jiansheng Yang, Zhouchen Lin

ICCVW 2017 Deep Domain Adaptation by Geodesic Distance Minimization Yifei Wang, Wen Li, Dengxin Dai, Luc Van Gool