Chuan Guo - RankMe

105 papers A* 27A 8Journal 66Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	IH-Challenge: A Training Dataset to Improve Instruction Hierarchy on Frontier LLMs. CoRR Chuan Guo, Juan Felipe Ceron Uribe, Sicheng Zhu, Christopher A. Choquette-Choo, Stephanie Lin, Nikhil Kandpal, Milad Nasr, Rai, Sam Toyer, Miles Wang, Yaodong Yu, Alex Beutel, Kai Xiao
2026	J	`jnl`	LLaMo: Scaling Pretrained Language Models for Unified Motion Understanding and Generation with Continuous Autoregressive Tokens. CoRR Zekun Li, Sizhe An, Chengcheng Tang, Chuan Guo, Ivan Shugurov, Linguang Zhang, Amy Zhao, Srinath Sridhar, Lingling Tao, Abhay Mittal
2025	A*	`conf`	AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs. ICML Anselm Paulus, Arman Zharmagambetov, Chuan Guo, Brandon Amos, Yuandong Tian
2025	J	`jnl`	AgentDAM: Privacy Leakage Evaluation for Autonomous Web Agents. CoRR Arman Zharmagambetov, Chuan Guo, Ivan Evtimov, Maya Pavlova, Ruslan Salakhutdinov, Kamalika Chaudhuri
2025	J	`jnl`	Detecting Benchmark Contamination Through Watermarking. CoRR Tom Sander, Pierre Fernandez, Saeed Mahloujifar, Alain Durmus, Chuan Guo
2025	J	`jnl`	How much do language models memorize? CoRR John X. Morris, Chawin Sitawarin, Chuan Guo, Narine Kokhlikyan, G. Edward Suh, Alexander M. Rush, Kamalika Chaudhuri, Saeed Mahloujifar
2025	A*	`conf`	Machine Learning with Privacy for Protected Attributes. SP Saeed Mahloujifar, Chuan Guo, G. Edward Suh, Kamalika Chaudhuri
2025	J	`jnl`	Machine Learning with Privacy for Protected Attributes. CoRR Saeed Mahloujifar, Chuan Guo, G. Edward Suh, Kamalika Chaudhuri
2025	J	`jnl`	Measuring Déjà vu Memorization Efficiently. CoRR Narine Kokhlikyan, Bargav Jayaraman, Florian Bordes, Chuan Guo, Kamalika Chaudhuri
2025	J	`jnl`	Meta SecAlign: A Secure Foundation LLM Against Prompt Injection Attacks. CoRR Sizhe Chen, Arman Zharmagambetov, David A. Wagner, Chuan Guo
2025	J	`jnl`	Privacy Blur: Quantifying Privacy and Utility for Image Data Release. CoRR Saeed Mahloujifar, Narine Kokhlikyan, Chuan Guo, Kamalika Chaudhuri
2025	J	`jnl`	RL Is a Hammer and LLMs Are Nails: A Simple Reinforcement Learning Recipe for Strong Prompt Injection. CoRR Yuxin Wen, Arman Zharmagambetov, Ivan Evtimov, Narine Kokhlikyan, Tom Goldstein, Kamalika Chaudhuri, Chuan Guo
2025	J	`jnl`	RoFL: Robust Fingerprinting of Language Models. CoRR Yun-Yun Tsai, Chuan Guo, Junfeng Yang, Laurens van der Maaten
2025	A*	`conf`	SecAlign: Defending Against Prompt Injection with Preference Optimization. CCS Sizhe Chen, Arman Zharmagambetov, Saeed Mahloujifar, Kamalika Chaudhuri, David A. Wagner, Chuan Guo
2025	J	`jnl`	Unlocking Visual Secrets: Inverting Features with Diffusion Priors for Image Reconstruction. Trans. Mach. Learn. Res. Sai Qian Zhang, Ziyun Li, Chuan Guo, Saeed Mahloujifar, Deeksha Dangwal, G. Edward Suh, Barbara De Salvo, Chiao Liu
2025	J	`jnl`	WASP: Benchmarking Web Agent Security Against Prompt Injection Attacks. CoRR Ivan Evtimov, Arman Zharmagambetov, Aaron Grattafiori, Chuan Guo, Kamalika Chaudhuri
2024	J	`jnl`	AdvPrefix: An Objective for Nuanced LLM Jailbreaks. CoRR Sicheng Zhu, Brandon Amos, Yuandong Tian, Chuan Guo, Ivan Evtimov
2024	J	`jnl`	AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs. CoRR Anselm Paulus, Arman Zharmagambetov, Chuan Guo, Brandon Amos, Yuandong Tian
2024	J	`jnl`	Aligning LLMs to Be Robust Against Prompt Injection. CoRR Sizhe Chen, Arman Zharmagambetov, Saeed Mahloujifar, Kamalika Chaudhuri, Chuan Guo
2024	J	`jnl`	An Introduction to Vision-Language Modeling. CoRR Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe, Vasu Sharma, Hu Xu, Xiaoqing Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari Hemmat, Jun Chen, Kushal Tirumala, Rim Assouel, Mazda Moayeri, Arjang Talattof, Kamalika Chaudhuri, Zechun Liu, Xilun Chen, Quentin Garrido, Karen Ullrich, Aishwarya Agrawal, Kate Saenko, Asli Celikyilmaz, Vikas Chandra
2024	J	`jnl`	DP-RDM: Adapting Diffusion Models to Private Domains Without Fine-Tuning. CoRR Jonathan Lebensold, Maziar Sanjabi, Pietro Astolfi, Adriana Romero-Soriano, Kamalika Chaudhuri, Mike Rabbat, Chuan Guo
2024	A*	`conf`	Differentially Private Representation Learning via Image Captioning. ICML Tom Sander, Yaodong Yu, Maziar Sanjabi, Alain Oliviero Durmus, Yi Ma, Kamalika Chaudhuri, Chuan Guo
2024	J	`jnl`	Differentially Private Representation Learning via Image Captioning. CoRR Tom Sander, Yaodong Yu, Maziar Sanjabi, Alain Durmus, Yi Ma, Kamalika Chaudhuri, Chuan Guo
2024	A*	`conf`	Déjà Vu Memorization in Vision-Language Models. NeurIPS Bargav Jayaraman, Chuan Guo, Kamalika Chaudhuri
2024	J	`jnl`	Déjà Vu Memorization in Vision-Language Models. CoRR Bargav Jayaraman, Chuan Guo, Kamalika Chaudhuri
2024	J	`jnl`	Guarantees of confidentiality via Hammersley-Chapman-Robbins bounds. CoRR Kamalika Chaudhuri, Chuan Guo, Laurens van der Maaten, Saeed Mahloujifar, Mark Tygert
2024	J	`jnl`	Guarantees of confidentiality via Hammersley-Chapman-Robbins bounds. Trans. Mach. Learn. Res. Kamalika Chaudhuri, Chuan Guo, Laurens van der Maaten, Saeed Mahloujifar, Mark Tygert
2024	A*	`conf`	Information Flow Control in Machine Learning through Modular Model Architecture. USENIX Security Symposium Trishita Tiwari, Suchin Gururangan, Chuan Guo, Weizhe Hua, Sanjay Kariyappa, Udit Gupta, Wenjie Xiong, Kiwan Maeng, Hsien-Hsin S. Lee, G. Edward Suh
2024	A*	`conf`	Measuring Dejavu Memorization Efficiently. NeurIPS Narine Kokhlikyan, Bargav Jayaraman, Florian Bordes, Chuan Guo, Kamalika Chaudhuri
2024	J	`jnl`	Privacy Amplification for the Gaussian Mechanism via Bounded Support. CoRR Shengyuan Hu, Saeed Mahloujifar, Virginia Smith, Kamalika Chaudhuri, Chuan Guo
2024	J	`jnl`	Unlocking Visual Secrets: Inverting Features with Diffusion Priors for Image Reconstruction. CoRR Sai Qian Zhang, Ziyun Li, Chuan Guo, Saeed Mahloujifar, Deeksha Dangwal, G. Edward Suh, Barbara De Salvo, Chiao Liu
2024	A*	`conf`	ViP: A Differentially Private Foundation Model for Computer Vision. ICML Yaodong Yu, Maziar Sanjabi, Yi Ma, Kamalika Chaudhuri, Chuan Guo
2023	J	`jnl`	"Private Prediction Strikes Back!" Private Kernelized Nearest Neighbors with Individual Renyi Filter. CoRR Yuqing Zhu, Xuandong Zhao, Chuan Guo, Yu-Xiang Wang
2023	A*	`conf`	Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano. ICML Chuan Guo, Alexandre Sablayrolles, Maziar Sanjabi
2023	A*	`conf`	Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information. NeurIPS Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh
2023	J	`jnl`	Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information. CoRR Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh
2023	A*	`conf`	Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis. ICML Sanjay Kariyappa, Chuan Guo, Kiwan Maeng, Wenjie Xiong, G. Edward Suh, Moinuddin K. Qureshi, Hsien-Hsin S. Lee
2023	A*	`conf`	Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning. NeurIPS Casey Meehan, Florian Bordes, Pascal Vincent, Kamalika Chaudhuri, Chuan Guo
2023	J	`jnl`	Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning. CoRR Casey Meehan, Florian Bordes, Pascal Vincent, Kamalika Chaudhuri, Chuan Guo
2023	A	`conf`	Does Label Differential Privacy Prevent Label Inference Attacks? AISTATS Ruihan Wu, Jin Peng Zhou, Kilian Q. Weinberger, Chuan Guo
2023	J	`jnl`	Information Flow Control in Machine Learning through Modular Model Architecture. CoRR Trishita Tiwari, Suchin Gururangan, Chuan Guo, Weizhe Hua, Sanjay Kariyappa, Udit Gupta, Wenjie Xiong, Kiwan Maeng, Hsien-Hsin S. Lee, G. Edward Suh
2023	J	`jnl`	Large-Scale Public Data Improves Differentially Private Image Generation Quality. CoRR Ruihan Wu, Chuan Guo, Kamalika Chaudhuri
2023	A	`conf`	Learning To Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning. UAI Ruihan Wu, Xiangyu Chen, Chuan Guo, Kilian Q. Weinberger
2023	A	`conf`	Origins of Low-Dimensional Adversarial Perturbations. AISTATS Elvis Dohmatob, Chuan Guo, Morgane Goibert
2023	A*	`conf`	Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design. ICML Chuan Guo, Kamalika Chaudhuri, Pierre Stock, Michael G. Rabbat
2023	A	`conf`	Private Prediction Strikes Back! Private Kernelized Nearest Neighbors with Individual Rényi Filter. UAI Yuqing Zhu, Xuandong Zhao, Chuan Guo, Yu-Xiang Wang
2023	J	`jnl`	ViP: A Differentially Private Foundation Model for Computer Vision. CoRR Yaodong Yu, Maziar Sanjabi, Yi Ma, Kamalika Chaudhuri, Chuan Guo
2022	J	`jnl`	Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano. CoRR Chuan Guo, Alexandre Sablayrolles, Maziar Sanjabi
2022	A*	`conf`	Bounding Training Data Reconstruction in Private (Deep) Learning. ICML Chuan Guo, Brian Karrer, Kamalika Chaudhuri, Laurens van der Maaten
2022	J	`jnl`	Bounding Training Data Reconstruction in Private (Deep) Learning. CoRR Chuan Guo, Brian Karrer, Kamalika Chaudhuri, Laurens van der Maaten
2022	J	`jnl`	Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component Analysis. CoRR Sanjay Kariyappa, Chuan Guo, Kiwan Maeng, Wenjie Xiong, G. Edward Suh, Moinuddin K. Qureshi, Hsien-Hsin S. Lee
2022	J	`jnl`	Does Label Differential Privacy Prevent Label Inference Attacks? CoRR Ruihan Wu, Jin Peng Zhou, Kilian Q. Weinberger, Chuan Guo
2022	A*	`conf`	EIFFeL: Ensuring Integrity for Federated Learning. CCS Amrita Roy Chowdhury, Chuan Guo, Somesh Jha, Laurens van der Maaten
2022	J	`jnl`	Learning to Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning. CoRR Ruihan Wu, Xiangyu Chen, Chuan Guo, Kilian Q. Weinberger
2022	A*	`conf`	Measuring Data Leakage in Machine-Learning Models with Fisher Information (Extended Abstract). IJCAI Awni Y. Hannun, Chuan Guo, Laurens van der Maaten
2022	J	`jnl`	Measuring and Controlling Split Layer Privacy Leakage Using Fisher Information. CoRR Kiwan Maeng, Chuan Guo, Sanjay Kariyappa, G. Edward Suh
2022	A*	`conf`	On the Importance of Difficulty Calibration in Membership Inference Attacks. ICLR Lauren Watson, Chuan Guo, Graham Cormode, Alexandre Sablayrolles
2022	J	`jnl`	Origins of Low-dimensional Adversarial Perturbations. CoRR Elvis Dohmatob, Chuan Guo, Morgane Goibert
2022	J	`jnl`	Privacy-Aware Compression for Federated Data Analysis. CoRR Kamalika Chaudhuri, Chuan Guo, Mike Rabbat
2022	A	`conf`	Privacy-aware compression for federated data analysis. UAI Kamalika Chaudhuri, Chuan Guo, Mike Rabbat
2022	J	`jnl`	Submix: Practical Private Prediction for Large-Scale Language Models. CoRR Antonio Ginart, Laurens van der Maaten, James Zou, Chuan Guo
2022	J	`jnl`	The Interpolated MVU Mechanism For Communication-efficient Private Federated Learning. CoRR Chuan Guo, Kamalika Chaudhuri, Pierre Stock, Mike Rabbat
2021	A*	`conf`	BulletTrain: Accelerating Robust Neural Network Training via Boundary Example Mining. NeurIPS Weizhe Hua, Yichi Zhang, Chuan Guo, Zhiru Zhang, G. Edward Suh
2021	J	`jnl`	BulletTrain: Accelerating Robust Neural Network Training via Boundary Example Mining. CoRR Weizhe Hua, Yichi Zhang, Chuan Guo, Zhiru Zhang, G. Edward Suh
2021	J	`jnl`	Byzantine-Robust and Privacy-Preserving Framework for FedML. CoRR Hanieh Hashemi, Yongqin Wang, Chuan Guo, Murali Annavaram
2021	J	`jnl`	EIFFeL: Ensuring Integrity for Federated Learning. CoRR Amrita Roy Chowdhury, Chuan Guo, Somesh Jha, Laurens van der Maaten
2021	A*	`conf`	Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems. NeurIPS Ruihan Wu, Chuan Guo, Awni Y. Hannun, Laurens van der Maaten
2021	J	`jnl`	Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems. CoRR Ruihan Wu, Chuan Guo, Awni Y. Hannun, Laurens van der Maaten
2021	—	`conf`	Gradient-based Adversarial Attacks against Text Transformers. EMNLP (1) Chuan Guo, Alexandre Sablayrolles, Hervé Jégou, Douwe Kiela
2021	J	`jnl`	Gradient-based Adversarial Attacks against Text Transformers. CoRR Chuan Guo, Alexandre Sablayrolles, Hervé Jégou, Douwe Kiela
2021	A*	`conf`	Making Paper Reviewing Robust to Bid Manipulation Attacks. ICML Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens van der Maaten, Kilian Q. Weinberger
2021	J	`jnl`	Making Paper Reviewing Robust to Bid Manipulation Attacks. CoRR Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens van der Maaten, Kilian Q. Weinberger
2021	J	`jnl`	Measuring Data Leakage in Machine-Learning Models with Fisher Information. CoRR Awni Y. Hannun, Chuan Guo, Laurens van der Maaten
2021	A	`conf`	Measuring data leakage in machine-learning models with Fisher information. UAI Awni Y. Hannun, Chuan Guo, Laurens van der Maaten
2021	J	`jnl`	On the Importance of Difficulty Calibration in Membership Inference Attacks. CoRR Lauren Watson, Chuan Guo, Graham Cormode, Alexandre Sablayrolles
2021	A*	`conf`	Online Adaptation to Label Distribution Shift. NeurIPS Ruihan Wu, Chuan Guo, Yi Su, Kilian Q. Weinberger
2021	J	`jnl`	Online Adaptation to Label Distribution Shift. CoRR Ruihan Wu, Chuan Guo, Yi Su, Kilian Q. Weinberger
2021	A*	`conf`	ReAct: Out-of-distribution Detection With Rectified Activations. NeurIPS Yiyou Sun, Chuan Guo, Yixuan Li
2021	J	`jnl`	ReAct: Out-of-distribution Detection With Rectified Activations. CoRR Yiyou Sun, Chuan Guo, Yixuan Li
2020	A*	`conf`	Certified Data Removal from Machine Learning Models. ICML Chuan Guo, Tom Goldstein, Awni Y. Hannun, Laurens van der Maaten
2020	J	`jnl`	Secure multiparty computations in floating-point arithmetic. CoRR Chuan Guo, Awni Y. Hannun, Brian Knott, Laurens van der Maaten, Mark Tygert, Ruiyu Zhu
2020	—	`—`	Threats and Countermeasures in Machine Learning Applications. Chuan Guo
2020	J	`jnl`	TrojanNet: Embedding Hidden Trojan Horse Models in Neural Networks. CoRR Chuan Guo, Ruihan Wu, Kilian Q. Weinberger
2019	A*	`conf`	A New Defense Against Adversarial Images: Turning a Weakness into a Strength. NeurIPS Shengyuan Hu, Tao Yu, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger
2019	J	`jnl`	A New Defense Against Adversarial Images: Turning a Weakness into a Strength. CoRR Tao Yu, Shengyuan Hu, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger
2019	A*	`conf`	Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces. NeurIPS Chuan Guo, Ali Mousavi, Xiang Wu, Daniel Niels Holtmann-Rice, Satyen Kale, Sashank J. Reddi, Sanjiv Kumar
2019	J	`jnl`	Certified Data Removal from Machine Learning Models. CoRR Chuan Guo, Tom Goldstein, Awni Y. Hannun, Laurens van der Maaten
2019	A	`conf`	Low Frequency Adversarial Perturbation. UAI Chuan Guo, Jared S. Frank, Kilian Q. Weinberger
2019	A*	`conf`	Simple Black-box Adversarial Attacks. ICML Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger
2019	J	`jnl`	Simple Black-box Adversarial Attacks. CoRR Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger
2018	J	`jnl`	An empirical study on evaluation metrics of generative adversarial networks. CoRR Qiantong Xu, Gao Huang, Yang Yuan, Chuan Guo, Yu Sun, Felix Wu, Kilian Q. Weinberger
2018	—	`conf`	Countering Adversarial Images using Input Transformations. ICLR (Poster) Chuan Guo, Mayank Rana, Moustapha Cissé, Laurens van der Maaten
2018	J	`jnl`	Low Frequency Adversarial Perturbation. CoRR Chuan Guo, Jared S. Frank, Kilian Q. Weinberger
2018	J	`jnl`	On the b-chromatic number of cartesian products. Discret. Appl. Math. Chuan Guo, Mike Newman
2017	J	`jnl`	A tight bound on the size of certain separating hash families. Australas. J Comb. Chuan Guo, Douglas R. Stinson
2017	J	`jnl`	Countering Adversarial Images using Input Transformations. CoRR Chuan Guo, Mayank Rana, Moustapha Cissé, Laurens van der Maaten
2017	A	`conf`	Discovering and Exploiting Additive Structure for Bayesian Optimization. AISTATS Jacob R. Gardner, Chuan Guo, Kilian Q. Weinberger, Roman Garnett, Roger B. Grosse
2017	A*	`conf`	On Calibration of Modern Neural Networks. ICML Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger
2017	J	`jnl`	On Calibration of Modern Neural Networks. CoRR Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger
2016	J	`jnl`	Palindromic rich words and run-length encodings. Inf. Process. Lett. Chuan Guo, Jeffrey O. Shallit, Arseny M. Shur
2016	—	`conf`	Supervised Word Mover's Distance. NIPS Gao Huang, Chuan Guo, Matt J. Kusner, Yu Sun, Fei Sha, Kilian Q. Weinberger
2015	J	`jnl`	A tight bound on the size of certain separating hash families. CoRR Chuan Guo, Douglas R. Stinson
2015	J	`jnl`	On the Combinatorics of Palindromes and Antipalindromes. CoRR Chuan Guo, Jeffrey O. Shallit, Arseny M. Shur
2015	J	`jnl`	On tight bounds for binary frameproof codes. Des. Codes Cryptogr. Chuan Guo, Douglas R. Stinson, Tran van Trung
2014	J	`jnl`	On tight bounds for binary frameproof codes. CoRR Chuan Guo, Douglas R. Stinson, Tran van Trung