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ORCIDYue Xing 0002
Person information
- affiliation: Purdue University, Department of Statistics, IN, USA
Other persons with the same name
- Yue Xing — disambiguation page
- Yue Xing 0001
![[0000-0001-7422-3352]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-7422-3352")
— Princeton University, Department of Electrical Engineering, NJ, USA (and 1 more) - Yue Xing 0003 — University of Nottingham, School of Medicine, UK
- Yue Xing 0004 — North China Electric Power University, National Thermal Power Engineering & Technology Research Center, Beijing, China
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2020 – today
- 2024
[c13]Shenglai Zeng, Yaxin Li, Jie Ren, Yiding Liu, Han Xu, Pengfei He, Yue Xing, Shuaiqiang Wang, Jiliang Tang, Dawei Yin:
Exploring Memorization in Fine-tuned Language Models. ACL (1) 2024: 3917-3948- [c12]Shenglai Zeng, Jiankun Zhang, Pengfei He, Yiding Liu, Yue Xing, Han Xu, Jie Ren, Yi Chang, Shuaiqiang Wang, Dawei Yin, Jiliang Tang:
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG). ACL (Findings) 2024: 4505-4524 - [c11]Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng:
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. AISTATS 2024: 199-207 - [c10]Rajdeep Haldar, Yue Xing, Qifan Song:
Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability. AISTATS 2024: 1090-1098 - [c9]Jie Ren, Yaxin Li, Shenglai Zeng, Han Xu, Lingjuan Lyu, Yue Xing, Jiliang Tang:
Unveiling and Mitigating Memorization in Text-to-Image Diffusion Models Through Cross Attention. ECCV (77) 2024: 340-356 - [i22]Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng:
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. CoRR abs/2401.15248 (2024) - [i21]Yingqian Cui, Jie Ren, Pengfei He, Jiliang Tang, Yue Xing:
Superiority of Multi-Head Attention in In-Context Linear Regression. CoRR abs/2401.17426 (2024) - [i20]Yue Xing, Xiaofeng Lin, Namjoon Suh, Qifan Song, Guang Cheng:
Benefits of Transformer: In-Context Learning in Linear Regression Tasks with Unstructured Data. CoRR abs/2402.00743 (2024) - [i19]Pengfei He, Han Xu, Yue Xing, Hui Liu, Makoto Yamada, Jiliang Tang:
Data Poisoning for In-context Learning. CoRR abs/2402.02160 (2024) - [i18]Shenglai Zeng, Jiankun Zhang, Pengfei He, Yue Xing, Yiding Liu, Han Xu, Jie Ren, Shuaiqiang Wang, Dawei Yin, Yi Chang, Jiliang Tang:
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG). CoRR abs/2402.16893 (2024) - [i17]Rajdeep Haldar, Yue Xing, Qifan Song:
Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability. CoRR abs/2403.03967 (2024) - [i16]Jie Ren, Yaxin Li, Shenglai Zeng, Han Xu, Lingjuan Lyu, Yue Xing, Jiliang Tang:
Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention. CoRR abs/2403.11052 (2024) - [i15]Yuping Lin, Pengfei He, Han Xu, Yue Xing, Makoto Yamada, Hui Liu, Jiliang Tang:
Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis. CoRR abs/2406.10794 (2024) - [i14]Jie Ren, Yingqian Cui, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu:
EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations. CoRR abs/2406.13933 (2024) - [i13]Shenglai Zeng, Jiankun Zhang, Pengfei He, Jie Ren, Tianqi Zheng, Hanqing Lu, Han Xu, Hui Liu, Yue Xing, Jiliang Tang:
Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data. CoRR abs/2406.14773 (2024) - [i12]Jie Ren, Kangrui Chen, Yingqian Cui, Shenglai Zeng, Hui Liu, Yue Xing, Jiliang Tang, Lingjuan Lyu:
Six-CD: Benchmarking Concept Removals for Benign Text-to-image Diffusion Models. CoRR abs/2406.14855 (2024) - 2023
- [j2]Tony Sit, Yue Xing:
Distributed Censored Quantile Regression. J. Comput. Graph. Stat. 32(4): 1685-1697 (2023) - [i11]Yingqian Cui, Jie Ren, Yuping Lin, Han Xu, Pengfei He, Yue Xing, Wenqi Fan, Hui Liu, Jiliang Tang:
FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models. CoRR abs/2310.02401 (2023) - [i10]Pengfei He, Han Xu, Yue Xing, Jie Ren, Yingqian Cui, Shenglai Zeng, Jiliang Tang, Makoto Yamada, Mohammad Sabokrou:
Confidence-driven Sampling for Backdoor Attacks. CoRR abs/2310.05263 (2023) - [i9]Shenglai Zeng, Yaxin Li, Jie Ren, Yiding Liu, Han Xu, Pengfei He, Yue Xing, Shuaiqiang Wang, Jiliang Tang, Dawei Yin:
Exploring Memorization in Fine-tuned Language Models. CoRR abs/2310.06714 (2023) - 2022
- [j1]Yue Xing, Qifan Song, Guang Cheng:
Benefit of Interpolation in Nearest Neighbor Algorithms. SIAM J. Math. Data Sci. 4(2): 935-956 (2022) - [c8]Yue Xing, Qifan Song, Guang Cheng:
Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. AISTATS 2022: 136-168 - [c7]Yue Xing, Qifan Song, Guang Cheng:
Why Do Artificially Generated Data Help Adversarial Robustness. NeurIPS 2022 - [c6]Yue Xing, Qifan Song, Guang Cheng:
Phase Transition from Clean Training to Adversarial Training. NeurIPS 2022 - [i8]Yue Xing, Qifan Song, Guang Cheng:
Unlabeled Data Help: Minimax Analysis and Adversarial Robustness. CoRR abs/2202.06996 (2022) - [i7]Yue Xing, Qifan Song, Guang Cheng:
Benefit of Interpolation in Nearest Neighbor Algorithms. CoRR abs/2202.11817 (2022) - 2021
- [c5]Yue Xing, Qifan Song, Guang Cheng:
Predictive Power of Nearest Neighbors Algorithm under Random Perturbation. AISTATS 2021: 496-504 - [c4]Yue Xing, Qifan Song, Guang Cheng:
On the Generalization Properties of Adversarial Training. AISTATS 2021: 505-513 - [c3]Yue Xing, Ruizhi Zhang, Guang Cheng:
Adversarially Robust Estimate and Risk Analysis in Linear Regression. AISTATS 2021: 514-522 - [c2]Yue Xing, Qifan Song, Guang Cheng:
On the Algorithmic Stability of Adversarial Training. NeurIPS 2021: 26523-26535 - 2020
- [c1]Shih-Kang Chao, Zhanyu Wang, Yue Xing, Guang Cheng:
Directional Pruning of Deep Neural Networks. NeurIPS 2020 - [i6]Yue Xing, Qifan Song, Guang Cheng:
Predictive Power of Nearest Neighbors Algorithm under Random Perturbation. CoRR abs/2002.05304 (2020) - [i5]Shih-Kang Chao, Zhanyu Wang, Yue Xing, Guang Cheng:
Directional Pruning of Deep Neural Networks. CoRR abs/2006.09358 (2020) - [i4]Yue Xing, Qifan Song, Guang Cheng:
On the Generalization Properties of Adversarial Training. CoRR abs/2008.06631 (2020) - [i3]Yue Xing, Ruizhi Zhang, Guang Cheng:
Adversarially Robust Estimate and Risk Analysis in Linear Regression. CoRR abs/2012.10278 (2020)
2010 – 2019
- 2019
- [i2]Yue Xing, Qifan Song, Guang Cheng:
Benefit of Interpolation in Nearest Neighbor Algorithms. CoRR abs/1909.11720 (2019) - 2018
- [i1]Yue Xing, Qifan Song, Guang Cheng:
Statistical Optimality of Interpolated Nearest Neighbor Algorithms. CoRR abs/1810.02814 (2018)
Coauthor Index
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