Xing, Yue

21 publications

TMLR 2026 Adversarial Vulnerability from On-Manifold Inseparability and Poor Off-Manifold Convergence Rajdeep Haldar, Yue Xing, Qifan Song, Guang Lin

AISTATS 2025 A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration Yingqian Cui, Pengfei He, Xianfeng Tang, Qi He, Chen Luo, Jiliang Tang, Yue Xing

AISTATS 2025 Adversarial Training in High-Dimensional Regression: Generated Data and Neural Networks Yue Xing

NeurIPS 2025 Keeping an Eye on LLM Unlearning: The Hidden Risk and Remedy Jie Ren, Zhenwei Dai, Xianfeng Tang, Yue Xing, Shenglai Zeng, Hui Liu, Jingying Zeng, Qiankun Peng, Samarth Varshney, Suhang Wang, Qi He, Charu C. Aggarwal, Hui Liu

NeurIPS 2025 LLM Safety Alignment Is Divergence Estimation in Disguise Rajdeep Haldar, Ziyi Wang, Guang Lin, Yue Xing, Qifan Song

CVPR 2025 Six-CD: Benchmarking Concept Removals for Text-to-Image Diffusion Models Jie Ren, Kangrui Chen, Yingqian Cui, Shenglai Zeng, Hui Liu, Yue Xing, Jiliang Tang, Lingjuan Lyu

AISTATS 2025 Superiority of Multi-Head Attention: A Theoretical Study in Shallow Transformers in In-Context Linear Regression Yingqian Cui, Jie Ren, Pengfei He, Hui Liu, Jiliang Tang, Yue Xing

AISTATS 2024 Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng

AISTATS 2024 Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability Rajdeep Haldar, Yue Xing, Qifan Song

TMLR 2024 Stealthy Backdoor Attack via Confidence-Driven Sampling Pengfei He, Yue Xing, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Jiliang Tang, Makoto Yamada, Mohammad Sabokrou

NeurIPSW 2024 Towards the Effect of Examples on In-Context Learning: A Theoretical Case Study Pengfei He, Yingqian Cui, Han Xu, Hui Liu, Makoto Yamada, Jiliang Tang, Yue Xing

ECCV 2024 Unveiling and Mitigating Memorization in Text-to-Image Diffusion Models Through Cross Attention Jie Ren, Yaxin Li, Shenglai Zeng, Han Xu, Lingjuan Lyu, Yue Xing, Jiliang Tang

ICMLW 2023 Adversarial Training with Generated Data in High-Dimensional Regression: An Asymptotic Study Yue Xing

AISTATS 2022 Unlabeled Data Help: Minimax Analysis and Adversarial Robustness Yue Xing, Qifan Song, Guang Cheng

NeurIPS 2022 Phase Transition from Clean Training to Adversarial Training Yue Xing, Qifan Song, Guang Cheng

NeurIPS 2022 Why Do Artificially Generated Data Help Adversarial Robustness Yue Xing, Qifan Song, Guang Cheng

AISTATS 2021 Adversarially Robust Estimate and Risk Analysis in Linear Regression Yue Xing, Ruizhi Zhang, Guang Cheng

AISTATS 2021 On the Generalization Properties of Adversarial Training Yue Xing, Qifan Song, Guang Cheng

AISTATS 2021 Predictive Power of Nearest Neighbors Algorithm Under Random Perturbation Yue Xing, Qifan Song, Guang Cheng

NeurIPS 2021 On the Algorithmic Stability of Adversarial Training Yue Xing, Qifan Song, Guang Cheng

NeurIPS 2020 Directional Pruning of Deep Neural Networks Shih-Kang Chao, Zhanyu Wang, Yue Xing, Guang Cheng