Yue Xing - RankMe

80 papers A* 8A 8Journal 52Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adversarial Vulnerability from On-Manifold Inseparability and Poor Off-Manifold Convergence. Trans. Mach. Learn. Res. Rajdeep Haldar, Yue Xing, Qifan Song, Guang Lin
2026	J	`jnl`	How Do Latent Reasoning Methods Perform Under Weak and Strong Supervision? CoRR Yingqian Cui, Zhenwei Dai, Bing He, Zhan Shi, Hui Liu, Rui Sun, Zhiji Liu, Yue Xing, Jiliang Tang, Benoît Dumoulin
2026	—	`conf`	PEAR: Planner-Executor Agent Robustness Benchmark. EACL (Findings) Shen Dong, Mingxuan Zhang, Pengfei He, Li Ma, Bhavani Thuraisingham, Hui Liu, Yue Xing
2026	J	`jnl`	Retrieval Heads are Dynamic. CoRR Yuping Lin, Zitao Li, Yue Xing, Pengfei He, Yingqian Cui, Yaliang Li, Bolin Ding, Jingren Zhou, Jiliang Tang
2026	J	`jnl`	f-GRPO and Beyond: Divergence-Based Reinforcement Learning Algorithms for General LLM Alignment. CoRR Rajdeep Haldar, Lantao Mei, Guang Lin, Yue Xing, Qifan Song
2025	—	`conf`	A General Framework to Enhance Fine-tuning-based LLM Unlearning. ACL (Findings) Jie Ren, Zhenwei Dai, Xianfeng Tang, Hui Liu, Jingying Zeng, Zhen Li, Rahul Goutam, Suhang Wang, Yue Xing, Qi He
2025	J	`jnl`	A General Framework to Enhance Fine-tuning-based LLM Unlearning. CoRR Jie Ren, Zhenwei Dai, Xianfeng Tang, Hui Liu, Jingying Zeng, Zhen Li, Rahul Goutam, Suhang Wang, Yue Xing, Qi He
2025	A	`conf`	A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration. AISTATS Yingqian Cui, Pengfei He, Xianfeng Tang, Qi He, Chen Luo, Jiliang Tang, Yue Xing
2025	J	`jnl`	Adaptive Test-Time Reasoning via Reward-Guided Dual-Phase Search. CoRR Yingqian Cui, Zhenwei Dai, Pengfei He, Bing He, Hui Liu, Xianfeng Tang, Jingying Zeng, Suhang Wang, Yue Xing, Jiliang Tang, Benoît Dumoulin
2025	—	`conf`	Advancing Reasoning with Off-the-Shelf LLMs: A Semantic Structure Perspective. EMNLP (Findings) Pengfei He, Zitao Li, Yue Xing, Yaliang Li, Jiliang Tang, Bolin Ding
2025	J	`jnl`	Attention Knows Whom to Trust: Attention-based Trust Management for LLM Multi-Agent Systems. CoRR Pengfei He, Zhenwei Dai, Xianfeng Tang, Yue Xing, Hui Liu, Jingying Zeng, Qiankun Peng, Shrivats Agrawal, Samarth Varshney, Suhang Wang, Jiliang Tang, Qi He
2025	J	`jnl`	Comprehensive Vulnerability Analysis is Necessary for Trustworthy LLM-MAS. CoRR Pengfei He, Yue Xing, Shen Dong, Juanhui Li, Zhenwei Dai, Xianfeng Tang, Hui Liu, Han Xu, Zhen Xiang, Charu C. Aggarwal
2025	—	`conf`	Data Poisoning for In-context Learning. NAACL (Findings) Pengfei He, Han Xu, Yue Xing, Hui Liu, Makoto Yamada, Jiliang Tang
2025	J	`jnl`	Keeping an Eye on LLM Unlearning: The Hidden Risk and Remedy. CoRR 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
2025	J	`jnl`	LLM Safety Alignment is Divergence Estimation in Disguise. CoRR Rajdeep Haldar, Ziyi Wang, Qifan Song, Guang Lin, Yue Xing
2025	A*	`conf`	Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data. EMNLP Shenglai Zeng, Jiankun Zhang, Pengfei He, Jie Ren, Tianqi Zheng, Hanqing Lu, Han Xu, Hui Liu, Yue Xing, Jiliang Tang
2025	J	`jnl`	Multi-Faceted Studies on Data Poisoning can Advance LLM Development. CoRR Pengfei He, Yue Xing, Han Xu, Zhen Xiang, Jiliang Tang
2025	J	`jnl`	PEAR: Planner-Executor Agent Robustness Benchmark. CoRR Shen Dong, Mingxuan Zhang, Pengfei He, Li Ma, Bhavani Thuraisingham, Hui Liu, Yue Xing
2025	—	`conf`	Red-Teaming LLM Multi-Agent Systems via Communication Attacks. ACL (Findings) Pengfei He, Yuping Lin, Shen Dong, Han Xu, Yue Xing, Hui Liu
2025	J	`jnl`	Red-Teaming LLM Multi-Agent Systems via Communication Attacks. CoRR Pengfei He, Yupin Lin, Shen Dong, Han Xu, Yue Xing, Hui Liu
2025	A*	`conf`	Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Model. WWW Jie Ren, Kangrui Chen, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu
2025	A*	`conf`	Six-CD: Benchmarking Concept Removals for Text-to-image Diffusion Models. CVPR Jie Ren, Kangrui Chen, Yingqian Cui, Shenglai Zeng, Hui Liu, Yue Xing, Jiliang Tang, Lingjuan Lyu
2025	J	`jnl`	SoK: Machine Unlearning for Large Language Models. CoRR Jie Ren, Yue Xing, Yingqian Cui, Charu C. Aggarwal, Hui Liu
2025	—	`conf`	Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models. ACL (Findings) 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
2025	J	`jnl`	Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models. CoRR 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
2025	A	`conf`	Superiority of Multi-Head Attention: A Theoretical Study in Shallow Transformers in In-Context Linear Regression. AISTATS Yingqian Cui, Jie Ren, Pengfei He, Hui Liu, Jiliang Tang, Yue Xing
2025	J	`jnl`	TRAJECT-Bench:A Trajectory-Aware Benchmark for Evaluating Agentic Tool Use. CoRR Pengfei He, Zhenwei Dai, Bing He, Hui Liu, Xianfeng Tang, Hanqing Lu, Juanhui Li, Jiayuan Ding, Subhabrata Mukherjee, Suhang Wang, Yue Xing, Jiliang Tang, Benoît Dumoulin
2025	—	`conf`	Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach. ACL (1) Shenglai Zeng, Pengfei He, Kai Guo, Tianqi Zheng, Hanqing Lu, Yue Xing, Hui Liu
2025	J	`jnl`	Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach. CoRR Shenglai Zeng, Pengfei He, Kai Guo, Tianqi Zheng, Hanqing Lu, Yue Xing, Hui Liu
2025	—	`conf`	Towards Knowledge Checking in Retrieval-augmented Generation: A Representation Perspective. NAACL (Long Papers) Shenglai Zeng, Jiankun Zhang, Bingheng Li, Yuping Lin, Tianqi Zheng, Dante Everaert, Hanqing Lu, Hui Liu, Yue Xing, Monica Xiao Cheng, Jiliang Tang
2025	—	`conf`	Unveiling Privacy Risks in LLM Agent Memory. ACL (1) Bo Wang, Weiyi He, Shenglai Zeng, Zhen Xiang, Yue Xing, Jiliang Tang, Pengfei He
2025	J	`jnl`	Unveiling Privacy Risks in LLM Agent Memory. CoRR Bo Wang, Weiyi He, Pengfei He, Shenglai Zeng, Zhen Xiang, Yue Xing, Jiliang Tang
2024	J	`jnl`	A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration. CoRR Yingqian Cui, Pengfei He, Xianfeng Tang, Qi He, Chen Luo, Jiliang Tang, Yue Xing
2024	J	`jnl`	Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility. CoRR Rajdeep Haldar, Yue Xing, Qifan Song, Guang Lin
2024	J	`jnl`	An Adversarially Robust Formulation of Linear Regression With Missing Data. IEEE Trans. Signal Process. Alireza Aghasi, Saeed Ghadimi, Yue Xing, MohammadJavad Feizollahi
2024	J	`jnl`	Benefits of Transformer: In-Context Learning in Linear Regression Tasks with Unstructured Data. CoRR Yue Xing, Xiaofeng Lin, Namjoon Suh, Qifan Song, Guang Cheng
2024	A	`conf`	Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. AISTATS Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng
2024	J	`jnl`	Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. CoRR Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng
2024	J	`jnl`	Data Poisoning for In-context Learning. CoRR Pengfei He, Han Xu, Yue Xing, Hui Liu, Makoto Yamada, Jiliang Tang
2024	J	`jnl`	DiffusionShield: A Watermark for Data Copyright Protection against Generative Diffusion Models. SIGKDD Explor. Yingqian Cui, Jie Ren, Han Xu, Pengfei He, Hui Liu, Lichao Sun, Yue Xing, Jiliang Tang
2024	A	`conf`	Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability. AISTATS Rajdeep Haldar, Yue Xing, Qifan Song
2024	J	`jnl`	Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability. CoRR Rajdeep Haldar, Yue Xing, Qifan Song
2024	J	`jnl`	EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations. CoRR Jie Ren, Yingqian Cui, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu
2024	—	`conf`	Exploring Memorization in Fine-tuned Language Models. ACL (1) Shenglai Zeng, Yaxin Li, Jie Ren, Yiding Liu, Han Xu, Pengfei He, Yue Xing, Shuaiqiang Wang, Jiliang Tang, Dawei Yin
2024	J	`jnl`	FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models. SIGKDD Explor. Yingqian Cui, Jie Ren, Yuping Lin, Han Xu, Pengfei He, Yue Xing, Lingjuan Lyu, Wenqi Fan, Hui Liu, Jiliang Tang
2024	J	`jnl`	Make LLMs better zero-shot reasoners: Structure-orientated autonomous reasoning. CoRR Pengfei He, Zitao Li, Yue Xing, Yaling Li, Jiliang Tang, Bolin Ding
2024	J	`jnl`	Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data. CoRR Shenglai Zeng, Jiankun Zhang, Pengfei He, Jie Ren, Tianqi Zheng, Hanqing Lu, Han Xu, Hui Liu, Yue Xing, Jiliang Tang
2024	J	`jnl`	Self-Comparison for Dataset-Level Membership Inference in Large (Vision-)Language Models. CoRR Jie Ren, Kangrui Chen, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu
2024	J	`jnl`	Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models. CoRR Jie Ren, Kangrui Chen, Yingqian Cui, Shenglai Zeng, Hui Liu, Yue Xing, Jiliang Tang, Lingjuan Lyu
2024	J	`jnl`	Stealthy Backdoor Attack via Confidence-driven Sampling. Trans. Mach. Learn. Res. Pengfei He, Yue Xing, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Jiliang Tang, Makoto Yamada, Mohammad Sabokrou
2024	J	`jnl`	Superiority of Multi-Head Attention in In-Context Linear Regression. CoRR Yingqian Cui, Jie Ren, Pengfei He, Jiliang Tang, Yue Xing
2024	—	`conf`	The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG). ACL (Findings) Shenglai Zeng, Jiankun Zhang, Pengfei He, Yiding Liu, Yue Xing, Han Xu, Jie Ren, Yi Chang, Shuaiqiang Wang, Dawei Yin, Jiliang Tang
2024	J	`jnl`	The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG). CoRR Shenglai Zeng, Jiankun Zhang, Pengfei He, Yue Xing, Yiding Liu, Han Xu, Jie Ren, Shuaiqiang Wang, Dawei Yin, Yi Chang, Jiliang Tang
2024	J	`jnl`	Towards Knowledge Checking in Retrieval-augmented Generation: A Representation Perspective. CoRR Shenglai Zeng, Jiankun Zhang, Bingheng Li, Yuping Lin, Tianqi Zheng, Dante Everaert, Hanqing Lu, Hui Liu, Yue Xing, Monica Xiao Cheng, Jiliang Tang
2024	A*	`conf`	Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis. EMNLP Yuping Lin, Pengfei He, Han Xu, Yue Xing, Makoto Yamada, Hui Liu, Jiliang Tang
2024	J	`jnl`	Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis. CoRR Yuping Lin, Pengfei He, Han Xu, Yue Xing, Makoto Yamada, Hui Liu, Jiliang Tang
2024	J	`jnl`	Towards the Effect of Examples on In-Context Learning: A Theoretical Case Study. CoRR Pengfei He, Yingqian Cui, Han Xu, Hui Liu, Makoto Yamada, Jiliang Tang, Yue Xing
2024	—	`conf`	Unveiling and Mitigating Memorization in Text-to-Image Diffusion Models Through Cross Attention. ECCV (77) Jie Ren, Yaxin Li, Shenglai Zeng, Han Xu, Lingjuan Lyu, Yue Xing, Jiliang Tang
2024	J	`jnl`	Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention. CoRR Jie Ren, Yaxin Li, Shenglai Zeng, Han Xu, Lingjuan Lyu, Yue Xing, Jiliang Tang
2023	J	`jnl`	Confidence-driven Sampling for Backdoor Attacks. CoRR Pengfei He, Han Xu, Yue Xing, Jie Ren, Yingqian Cui, Shenglai Zeng, Jiliang Tang, Makoto Yamada, Mohammad Sabokrou
2023	J	`jnl`	Distributed Censored Quantile Regression. J. Comput. Graph. Stat. Tony Sit, Yue Xing
2023	J	`jnl`	Exploring Memorization in Fine-tuned Language Models. CoRR Shenglai Zeng, Yaxin Li, Jie Ren, Yiding Liu, Han Xu, Pengfei He, Yue Xing, Shuaiqiang Wang, Jiliang Tang, Dawei Yin
2023	J	`jnl`	FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models. CoRR Yingqian Cui, Jie Ren, Yuping Lin, Han Xu, Pengfei He, Yue Xing, Wenqi Fan, Hui Liu, Jiliang Tang
2022	J	`jnl`	Benefit of Interpolation in Nearest Neighbor Algorithms. CoRR Yue Xing, Qifan Song, Guang Cheng
2022	J	`jnl`	Benefit of Interpolation in Nearest Neighbor Algorithms. SIAM J. Math. Data Sci. Yue Xing, Qifan Song, Guang Cheng
2022	A*	`conf`	Phase Transition from Clean Training to Adversarial Training. NeurIPS Yue Xing, Qifan Song, Guang Cheng
2022	A	`conf`	Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. AISTATS Yue Xing, Qifan Song, Guang Cheng
2022	J	`jnl`	Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. CoRR Yue Xing, Qifan Song, Guang Cheng
2022	A*	`conf`	Why Do Artificially Generated Data Help Adversarial Robustness. NeurIPS Yue Xing, Qifan Song, Guang Cheng
2021	A	`conf`	Adversarially Robust Estimate and Risk Analysis in Linear Regression. AISTATS Yue Xing, Ruizhi Zhang, Guang Cheng
2021	A*	`conf`	On the Algorithmic Stability of Adversarial Training. NeurIPS Yue Xing, Qifan Song, Guang Cheng
2021	A	`conf`	On the Generalization Properties of Adversarial Training. AISTATS Yue Xing, Qifan Song, Guang Cheng
2021	A	`conf`	Predictive Power of Nearest Neighbors Algorithm under Random Perturbation. AISTATS Yue Xing, Qifan Song, Guang Cheng
2020	J	`jnl`	Adversarially Robust Estimate and Risk Analysis in Linear Regression. CoRR Yue Xing, Ruizhi Zhang, Guang Cheng
2020	A*	`conf`	Directional Pruning of Deep Neural Networks. NeurIPS Shih-Kang Chao, Zhanyu Wang, Yue Xing, Guang Cheng
2020	J	`jnl`	Directional Pruning of Deep Neural Networks. CoRR Shih-Kang Chao, Zhanyu Wang, Yue Xing, Guang Cheng
2020	J	`jnl`	On the Generalization Properties of Adversarial Training. CoRR Yue Xing, Qifan Song, Guang Cheng
2020	J	`jnl`	Predictive Power of Nearest Neighbors Algorithm under Random Perturbation. CoRR Yue Xing, Qifan Song, Guang Cheng
2019	J	`jnl`	Benefit of Interpolation in Nearest Neighbor Algorithms. CoRR Yue Xing, Qifan Song, Guang Cheng
2018	J	`jnl`	Statistical Optimality of Interpolated Nearest Neighbor Algorithms. CoRR Yue Xing, Qifan Song, Guang Cheng