Knowledge Transfer

ACE: A model poisoning attack on contribution evaluation methods in federated learning

Xu, Z., Jiang, F., Niu, L., Jia, J., Li, Bo, Poovendran, Radha

33rd USENIX Security Symposium (USENIX Security 24), Philadelphia, Pennsylvania

Remote Keylogging Attacks in Multi-user VR Applications

Zihao Su, Kunlin Cai, Reuben Beeler, Lukas Dresel, Allan Garcia, Ilya Grishchenko, Yuan Tian, Christopher Kruegel, Giovanni Vigna

33rd USENIX Security Symposium (USENIX Security 24), Philadelphia, PA, August 14-16, 2024
 

SAIN: Improving ICS Attack Detection Sensitivity via State-Aware Invariants

Syed Ghazanfar Abbas, Muslum Ozgur Ozmen, Abdulellah Alsaheel, Arslan Khan,, Z. Berkay Celik, Dongyan Xu

33rd USENIX Security Symposium (USENIX Security 24), Philadelphia, PA, August 14-16, 2024
 

True Attacks, Attack Attempts, or Benign Triggers? An Empirical Measurement of Network Alerts in a Security Operations Center

Limin Yang, Zhi Chen, Chenkai Wang, Zhenning Zhang, Sushruth Booma, Phuong Cao, Constantin Adam, Alex Withers, Zbigniew Kalbarczyk, Ravishankar K. Iyer, Gang Wang

33rd USENIX Security Symposium (USENIX Security 24), Philadelphia, PA, August 14-16, 2024
 

MIST: Defending Against Membership Inference Attacks Through Membership-Invariant Subspace Training

Jiacheng Li, Ninghui Li, Bruno Ribeiro

33rd USENIX Security Symposium (USENIX Security 24), Philadelphia, PA, August 14-16, 2024

Rate, Explain and Cite (REC): Enhanced Explanation and Attribution in Automatic Evaluation by Large Language Models

Hsu, Aliyah R., ; Zhu, James, Wang, Zhichao, Bi, Bin, Mehrotra, Shubham, Pentyala, Shiva K., Tan, Katherine, Mao, Xiang-Bo, Omrani, Roshanak, Chaudhuri, Sougata, Radhakrishnan, Regunathan, Asur, Sitaram, Cheng, Claire Na, Yu, Bin

The 62nd Annual Meeting of the Association for Computational Linguistics (ACL)

Re-Tuning: Overcoming the Compositionality Limits of Large Language Models with Recursive Tuning

Pasewark, Eric, Montgomery, Kyle, Duan; Kefei, Song, Dawn, Wang, Chenguang

The 62nd Annual Meeting of the Association for Computational Linguistics (ACL)

SafeDecoding: Defending against jailbreak attacks via safety-aware decoding

Xu, Z., Jiang, F., Niu, L., Jia, J., Li, Bo, Poovendran, Radha

Annual Meeting of the Association for Computational Linguistics (ACL) Bangkok, Thailand

ArtPrompt: ASCII art-based jailbreak attacks against aligned LLMs

Jiang, F., Xu, Z., Niu, L., Xiang, Z., Li, Bo, Poovendran, Radha

Annual Meeting of the Association for Computational Linguistics (ACL), Bangkok, Thailand

Securing Deep Neural Networks on Edge from Membership Inference Attacks Using Trusted Execution Environments

Yang, Cheng-Yun, Ramshankar, Gowri, Nambiar, Sudarshan, Miller, Evan, Zhang, Xun, Eliopoulos, Nicholas, Jajal, Purvish, Jing Tian, Dave, Chen, Shuo-Han, Perng, Chiy-Ferng, Lu, Yung-Hsiang

2024 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), Newport Beach, California

Designing behavior-aware AI to improve the human-AI team performance in AI-assisted decision making

Mahmood, Syed Hasan Amin, Lu, Zhuoran, Yin, Ming

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, Jeju, Korea.

OODRobustbench: a benchmark and large-scale analysis of adversarial robustness under distribution shift

Li, L., Wang, Y., Sitawarin, C., Spratling, M.

Proceedings of the 41st International Conference on Machine Learning, Vienna, Austrian. May 2024.

RICE: Breaking Through the Training Bottlenecks of Reinforcement Learning with Explanation

Zelei Cheng, Xian Wu, Jiahao Yu, Sabrina Yang, Gang Wang, Xinyu Xing

International Conference on Machine Learning (ICML 2024), Vienna, Austria, July 21-27, 2024

Optimally Improving Cooperative Learning in a Social Setting

Shahrzad Haddadan, Cheng Xin, Jie Gao

International Conference on Machine Learning (ICML 2024), Vienna, Austria, July 21-27, 2024

Adversarial Images can Control Generative Models at Runtime

Luke Bailey, Euan Ong, Stuart Russell, Scott Emmons

International Conference on Machine Learning (ICML 2024), Vienna, Austria, July 21-27, 2024

InstructRetro: Instruction tuning post retrieval-augmented pretraining

Boxin Wang, Wei Ping, Lawrence McAfee, Peng Xu, Bo Li, Mohammad Shoeybi, Bryan Catanzaro

International Conference on Machine Learning (ICML 2024), Vienna Austria, July 21-27, 2024
 

Differentially private synthetic data via foundation model apis 2: Text

Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin A. Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin

International Conference on Machine Learning (ICML 2024), Vienna Austria, July 21-27, 2024
 

Universal consistency of wide and deep ReLU neural networks and minimax optimal convergence rates for Kolmogorov-Donoho optimal function classes

Hyunouk Ko, Xiaoming Huo

International Conference on Machine Learning (ICML 2024), Vienna Austria, July 21-27, 2024
 

Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression

Junyuan Hong, Jinhao Duan, Chenhui Zhang, Zhangheng Li, Chulin Xie, Kelsey Lieberman, James Diffenderfer , Brian Bartoldson , Ajay Jaiswal , Kaidi Xu , Bhavya Kailkhura , Dan Hendrycks , Dawn Song , Zhangyang Wang , Bo Li

International Conference on Machine Learning (ICML 2024), Vienna Austria, July 21-27, 2024
 

Harmbench: A standardized evaluation framework for automated red teaming and robust refusal

Mantas Mazeika, Long Phan, Xuwang Yin, Andy Zou, Zifan Wang, Norman Mu, Elham Sakhaee, Nathaniel Li , Steven Basart, Bo Li , David Forsyth , Dan Hendrycks

International Conference on Machine Learning (ICML 2024), Vienna Austria, July 21-27, 2024
 

C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models

Kang, Mintong, Nezihe Merve Gürel, Ning Yu, Dawn Song, Bo Li

International Conference on Machine Learning (ICML 2024), Vienna Austria, July 21-27, 2024
 

Certifiably Byzantine-Robust Federated Conformal Prediction

Mintong Kang, Zhen Lin, Jimeng Sun, Cao Xiao, Bo Li

International Conference on Machine Learning (ICML 2024), Vienna Austria, July 21-27, 2024
 

Grath: Gradual self-truthifying for large language models

Weixin Chen, Bo Li

International Conference on Machine Learning (ICML 2024), Vienna Austria, July 21-27, 2024
 

Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing

Youwei Shu, Xi Xiao, Derui Wang, Yuxin Xao, Siji Chen, Jason Xue, Linyi Li, Bo Li

International Conference on Machine Learning (ICML 2024), Vienna Austria, July 21-27, 2024
 

HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding

Zhaorun Chen, Zhuokai Zhao, Hongyin Luo, Huaxiu Yao, Bo Li, Jiawei Zhou

International Conference on Machine Learning (ICML 2024), Vienna Austria, July 21-27, 2024
 

SHINE: Shielding Backdoors in Deep Reinforcement Learning

Wenbo Guo, Zhuowen Yuan, Jinyuan Jia, Bo Li, Dawn Song

International Conference on Machine Learning (ICML 2024), Vienna Austria, July 21-27, 2024
 

RigorLLM: Resilient Guardrails for Large Language Models against Undesired Content

Yuan, Zhuowen, Zidi Xiong, Yi Zeng, Ning Yu, Ruoxi Jia, Dawn Song, and Bo Li

International Conference on Machine Learning (ICML 2024), Vienna Austria, July 21-27, 2024
 

DPzero: Dimension-independent and differentially private zeroth-order optimization

Liang Zhang, Kiran Koshy Thekumparampil, Sewoong Oh, Niao He

International Conference on Machine Learning (ICML 2024), Vienna Austria, July 21-27, 2024
 

LLM-PBE: Assessing Data Privacy in Large Language Models

Li, Qinbin, Hong, Junyuan, Xie, Chulin, Tan, Jeffrey, Xin, Rachel, Hou, Junyi, Yin, Xavier, Wang, Zhun, Hendrycks, Dan, Wang, Zhangyang, Li, Bo, He, Bingsheng, Song, Dawn

Proceedings of the VLDB Endowment, 17(11), Pages 3201 - 3214.July 1, 2024

Poster: Brave: Byzantine-resilient and privacy-preserving peer-to-peer federated learning

Xu, Z., Jiang, F., Niu, L., Jia, J., Li, Bo, Poovendran, Radha

In Proceedings of the 19th ACM Asia Conference on Computer and Communications Security (pp. 1934-1936). Singapore