Yue Xing

According to our database, Yue Xing authored at least 52 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

SoK: Machine Unlearning for Large Language Models.

Jie Ren, Yue Xing, Yingqian Cui, Charu C. Aggarwal, Hui Liu

CoRR, June, 2025

Attention Knows Whom to Trust: Attention-based Trust Management for LLM Multi-Agent Systems.

Pengfei He, Zhenwei Dai, Xianfeng Tang, Yue Xing, Hui Liu, Jingying Zeng, Qiankun Peng, Shrivats Agrawal, Samarth Varshney, Suhang Wang, Jiliang Tang, Qi He

CoRR, June, 2025

Comprehensive Vulnerability Analysis is Necessary for Trustworthy LLM-MAS.

Pengfei He, Yue Xing, Shen Dong, Juanhui Li, Zhenwei Dai, Xianfeng Tang, Hui Liu, Han Xu, Zhen Xiang, Charu C. Aggarwal, Hui Liu

CoRR, June, 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

CoRR, June, 2025

A General Framework to Enhance Fine-tuning-based LLM Unlearning.

Jie Ren, Zhenwei Dai, Xianfeng Tang, Hui Liu, Jingying Zeng, Zhen Li, Rahul Goutam, Suhang Wang, Yue Xing, Qi He

CoRR, February, 2025

Red-Teaming LLM Multi-Agent Systems via Communication Attacks.

Pengfei He, Yupin Lin, Shen Dong, Han Xu, Yue Xing, Hui Liu

CoRR, February, 2025

Multi-Faceted Studies on Data Poisoning can Advance LLM Development.

Pengfei He, Yue Xing, Han Xu, Zhen Xiang, Jiliang Tang

CoRR, February, 2025

Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models.

Yingqian Cui, Pengfei He, Jingying Zeng, Hui Liu, Xianfeng Tang, Zhenwei Dai, Yan Han, Chen Luo, Jing Huang, Zheng Li, Suhang Wang, Yue Xing, Jiliang Tang, Qi He

CoRR, February, 2025

LLM Safety Alignment is Divergence Estimation in Disguise.

Rajdeep Haldar, Ziyi Wang, Qifan Song, Guang Lin, Yue Xing

CoRR, February, 2025

Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Model.

Jie Ren, Kangrui Chen, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu

Proceedings of the ACM on Web Conference 2025, 2025

Towards Knowledge Checking in Retrieval-augmented Generation: A Representation Perspective.

Shenglai Zeng, Jiankun Zhang, Bingheng Li, Yuping Lin, Tianqi Zheng, Dante Everaert, Hanqing Lu, Hui Liu, Yue Xing, Monica Xiao Cheng, Jiliang Tang

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Data Poisoning for In-context Learning.

Pengfei He, Han Xu, Yue Xing, Hui Liu, Makoto Yamada, Jiliang Tang

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach.

Shenglai Zeng, Pengfei He, Kai Guo, Tianqi Zheng, Hanqing Lu, Yue Xing, Hui Liu

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Red-Teaming LLM Multi-Agent Systems via Communication Attacks.

Pengfei He, Yuping Lin, Shen Dong, Han Xu, Yue Xing, Hui Liu

Proceedings of the Findings of the Association for Computational Linguistics, 2025

Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models.

Yingqian Cui, Pengfei He, Jingying Zeng, Hui Liu, Xianfeng Tang, Zhenwei Dai, Yan Han, Chen Luo, Jing Huang, Zhen Li, Suhang Wang, Yue Xing, Jiliang Tang, Qi He

Proceedings of the Findings of the Association for Computational Linguistics, 2025

Unveiling Privacy Risks in LLM Agent Memory.

Bo Wang, Weiyi He, Shenglai Zeng, Zhen Xiang, Yue Xing, Jiliang Tang, Pengfei He

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

A General Framework to Enhance Fine-tuning-based LLM Unlearning.

Jie Ren, Zhenwei Dai, Xianfeng Tang, Hui Liu, Jingying Zeng, Zhen Li, Rahul Goutam, Suhang Wang, Yue Xing, Qi He

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

DiffusionShield: A Watermark for Data Copyright Protection against Generative Diffusion Models.

Yingqian Cui, Jie Ren, Han Xu, Pengfei He, Hui Liu, Lichao Sun, Yue Xing, Jiliang Tang

SIGKDD Explor., December, 2024

FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models.

Yingqian Cui, Jie Ren, Yuping Lin, Han Xu, Pengfei He, Yue Xing, Lingjuan Lyu, Wenqi Fan, Hui Liu, Jiliang Tang

SIGKDD Explor., December, 2024

An Adversarially Robust Formulation of Linear Regression With Missing Data.

Alireza Aghasi, Saeed Ghadimi, Yue Xing, MohammadJavad Feizollahi

IEEE Trans. Signal Process., 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

Trans. Mach. Learn. Res., 2024

Make LLMs better zero-shot reasoners: Structure-orientated autonomous reasoning.

Pengfei He, Zitao Li, Yue Xing, Yaling Li, Jiliang Tang, Bolin Ding

CoRR, 2024

Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Models.

Jie Ren, Kangrui Chen, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu

CoRR, 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

CoRR, 2024

Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility.

Rajdeep Haldar, Yue Xing, Qifan Song, Guang Lin

CoRR, 2024

Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models.

Jie Ren, Kangrui Chen, Yingqian Cui, Shenglai Zeng, Hui Liu, Yue Xing, Jiliang Tang, Lingjuan Lyu

CoRR, 2024

Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data.

Shenglai Zeng, Jiankun Zhang, Pengfei He, Jie Ren, Tianqi Zheng, Hanqing Lu, Han Xu, Hui Liu, Yue Xing, Jiliang Tang

CoRR, 2024

EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations.

Jie Ren, Yingqian Cui, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu

CoRR, 2024

Benefits of Transformer: In-Context Learning in Linear Regression Tasks with Unstructured Data.

Yue Xing, Xiaofeng Lin, Namjoon Suh, Qifan Song, Guang Cheng

CoRR, 2024

Superiority of Multi-Head Attention in In-Context Linear Regression.

Yingqian Cui, Jie Ren, Pengfei He, Jiliang Tang, Yue Xing

CoRR, 2024

Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis.

Yuping Lin, Pengfei He, Han Xu, Yue Xing, Makoto Yamada, Hui Liu, Jiliang Tang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 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

Proceedings of the Computer Vision - ECCV 2024, 2024

Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability.

Rajdeep Haldar, Yue Xing, Qifan Song

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective.

Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG).

Shenglai Zeng, Jiankun Zhang, Pengfei He, Yiding Liu, Yue Xing, Han Xu, Jie Ren, Yi Chang, Shuaiqiang Wang, Dawei Yin, Jiliang Tang

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Exploring Memorization in Fine-tuned Language Models.

Shenglai Zeng, Yaxin Li, Jie Ren, Yiding Liu, Han Xu, Pengfei He, Yue Xing, Shuaiqiang Wang, Jiliang Tang, Dawei Yin

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Distributed Censored Quantile Regression.

Tony Sit, Yue Xing

J. Comput. Graph. Stat., 2023

Confidence-driven Sampling for Backdoor Attacks.

Pengfei He, Han Xu, Yue Xing, Jie Ren, Yingqian Cui, Shenglai Zeng, Jiliang Tang, Makoto Yamada, Mohammad Sabokrou

CoRR, 2023

FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models.

Yingqian Cui, Jie Ren, Yuping Lin, Han Xu, Pengfei He, Yue Xing, Wenqi Fan, Hui Liu, Jiliang Tang

CoRR, 2023

2022

Benefit of Interpolation in Nearest Neighbor Algorithms.

Yue Xing, Qifan Song, Guang Cheng

SIAM J. Math. Data Sci., June, 2022

Phase Transition from Clean Training to Adversarial Training.

Yue Xing, Qifan Song, Guang Cheng

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Why Do Artificially Generated Data Help Adversarial Robustness.

Yue Xing, Qifan Song, Guang Cheng

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Unlabeled Data Help: Minimax Analysis and Adversarial Robustness.

Yue Xing, Qifan Song, Guang Cheng

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

On the Algorithmic Stability of Adversarial Training.

Yue Xing, Qifan Song, Guang Cheng

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adversarially Robust Estimate and Risk Analysis in Linear Regression.

Yue Xing, Ruizhi Zhang, Guang Cheng

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

On the Generalization Properties of Adversarial Training.

Yue Xing, Qifan Song, Guang Cheng

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Predictive Power of Nearest Neighbors Algorithm under Random Perturbation.

Yue Xing, Qifan Song, Guang Cheng

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Directional Pruning of Deep Neural Networks.

Shih-Kang Chao, Zhanyu Wang, Yue Xing, Guang Cheng

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2018

Statistical Optimality of Interpolated Nearest Neighbor Algorithms.

Yue Xing, Qifan Song, Guang Cheng

CoRR, 2018