Vikash Sehwag - RankMe

73 papers A* 21Journal 43Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Reliable and Responsible Foundation Models: A Comprehensive Survey. CoRR Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P. Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
2025	A*	`conf`	Adapting to Evolving Adversaries with Regularized Continual Robust Training. ICML Sihui Dai, Christian Cianfarani, Vikash Sehwag, Prateek Mittal, Arjun Nitin Bhagoji
2025	J	`jnl`	Adapting to Evolving Adversaries with Regularized Continual Robust Training. CoRR Sihui Dai, Christian Cianfarani, Arjun Nitin Bhagoji, Vikash Sehwag, Prateek Mittal
2025	A*	`conf`	Argus: A Compact and Versatile Foundation Model for Vision. CVPR Weiming Zhuang, Chen Chen, Zhizhong Li, Sina Sajadmanesh, Jingtao Li, Jiabo Huang, Vikash Sehwag, Vivek Sharma, Hirotaka Shinozaki, Felan Carlo Garcia, Yihao Zhan, Naohiro Adachi, Ryoji Eki, Michael Spranger, Peter Stone, Lingjuan Lyu
2025	A*	`conf`	CO-SPY: Combining Semantic and Pixel Features to Detect Synthetic Images by AI. CVPR Siyuan Cheng, Lingjuan Lyu, Zhenting Wang, Xiangyu Zhang, Vikash Sehwag
2025	J	`jnl`	CO-SPY: Combining Semantic and Pixel Features to Detect Synthetic Images by AI. CoRR Siyuan Cheng, Lingjuan Lyu, Zhenting Wang, Xiangyu Zhang, Vikash Sehwag
2025	J	`jnl`	Differentially Private Image Classification by Learning Priors from Random Processes. J. Priv. Confidentiality Xinyu Tang, Ashwinee Panda, Vikash Sehwag, Prateek Mittal
2025	J	`jnl`	Does More Inference-Time Compute Really Help Robustness? CoRR Tong Wu, Chong Xiang, Jiachen T. Wang, Weichen Yu, Chawin Sitawarin, Vikash Sehwag, Prateek Mittal
2025	J	`jnl`	FineGRAIN: Evaluating Failure Modes of Text-to-Image Models with Vision Language Model Judges. CoRR Kevin David Hayes, Micah Goldblum, Vikash Sehwag, Gowthami Somepalli, Ashwinee Panda, Tom Goldstein
2025	A*	`conf`	How to Evaluate and Mitigate IP Infringement in Visual Generative AI? ICML Zhenting Wang, Chen Chen, Vikash Sehwag, Minzhou Pan, Lingjuan Lyu
2025	J	`jnl`	PropensityBench: Evaluating Latent Safety Risks in Large Language Models via an Agentic Approach. CoRR Udari Madhushani Sehwag, Shayan Shabihi, Alex McAvoy, Vikash Sehwag, Yuancheng Xu, Dalton Towers, Furong Huang
2025	J	`jnl`	Reliable and Responsible Foundation Models. Trans. Mach. Learn. Res. Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P. Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Gordon Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
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`	Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget. CVPR Vikash Sehwag, Xianghao Kong, Jingtao Li, Michael Spranger, Lingjuan Lyu
2024	A*	`conf`	A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization. ICML Ashwinee Panda, Xinyu Tang, Saeed Mahloujifar, Vikash Sehwag, Prateek Mittal
2024	J	`jnl`	AI Risk Management Should Incorporate Both Safety and Security. CoRR Xiangyu Qi, Yangsibo Huang, Yi Zeng, Edoardo Debenedetti, Jonas Geiping, Luxi He, Kaixuan Huang, Udari Madhushani, Vikash Sehwag, Weijia Shi, Boyi Wei, Tinghao Xie, Danqi Chen, Pin-Yu Chen, Jeffrey Ding, Ruoxi Jia, Jiaqi Ma, Arvind Narayanan, Weijie J. Su, Mengdi Wang, Chaowei Xiao, Bo Li, Dawn Song, Peter Henderson, Prateek Mittal
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	J	`jnl`	Evaluating and Mitigating IP Infringement in Visual Generative AI. CoRR Zhenting Wang, Chen Chen, Vikash Sehwag, Minzhou Pan, Lingjuan Lyu
2024	—	`conf`	Finding Needles in a Haystack: A Black-Box Approach to Invisible Watermark Detection. ECCV (33) Minzhou Pan, Zhenting Wang, Xin Dong, Vikash Sehwag, Lingjuan Lyu, Xue Lin
2024	J	`jnl`	Finding needles in a haystack: A Black-Box Approach to Invisible Watermark Detection. CoRR Minzhou Pan, Zhenting Wang, Xin Dong, Vikash Sehwag, Lingjuan Lyu, Xue Lin
2024	A*	`conf`	How to Trace Latent Generative Model Generated Images without Artificial Watermark? ICML Zhenting Wang, Vikash Sehwag, Chen Chen, Lingjuan Lyu, Dimitris N. Metaxas, Shiqing Ma
2024	J	`jnl`	How to Trace Latent Generative Model Generated Images without Artificial Watermark? CoRR Zhenting Wang, Vikash Sehwag, Chen Chen, Lingjuan Lyu, Dimitris N. Metaxas, Shiqing Ma
2024	A*	`conf`	JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. NeurIPS Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, Eric Wong
2024	J	`jnl`	JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. CoRR Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, Eric Wong
2024	J	`jnl`	Masked Differential Privacy. CoRR David Schneider, Sina Sajadmanesh, Vikash Sehwag, M. Saquib Sarfraz, Rainer Stiefelhagen, Lingjuan Lyu, Vivek Sharma
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`	Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget. CoRR Vikash Sehwag, Xianghao Kong, Jingtao Li, Michael Spranger, Lingjuan Lyu
2023	—	`conf`	A Light Recipe to Train Robust Vision Transformers. SaTML Edoardo Debenedetti, Vikash Sehwag, Prateek Mittal
2023	A*	`conf`	Differentially Private Image Classification by Learning Priors from Random Processes. NeurIPS Xinyu Tang, Ashwinee Panda, Vikash Sehwag, Prateek Mittal
2023	J	`jnl`	Differentially Private Image Classification by Learning Priors from Random Processes. CoRR Xinyu Tang, Ashwinee Panda, Vikash Sehwag, Prateek Mittal
2023	A*	`conf`	Extracting Training Data from Diffusion Models. USENIX Security Symposium Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace
2023	J	`jnl`	Extracting Training Data from Diffusion Models. CoRR Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace
2023	A*	`conf`	MultiRobustBench: Benchmarking Robustness Against Multiple Attacks. ICML Sihui Dai, Saeed Mahloujifar, Chong Xiang, Vikash Sehwag, Pin-Yu Chen, Prateek Mittal
2023	J	`jnl`	MultiRobustBench: Benchmarking Robustness Against Multiple Attacks. CoRR Sihui Dai, Saeed Mahloujifar, Chong Xiang, Vikash Sehwag, Pin-Yu Chen, Prateek Mittal
2023	—	`—`	Promises and Pitfalls of Generative AI: An AI-Safety Centric Approach Vikash Sehwag
2023	J	`jnl`	Scaling Compute Is Not All You Need for Adversarial Robustness. CoRR Edoardo Debenedetti, Zishen Wan, Maksym Andriushchenko, Vikash Sehwag, Kshitij Bhardwaj, Bhavya Kailkhura
2023	A*	`conf`	Uncovering Adversarial Risks of Test-Time Adaptation. ICML Tong Wu, Feiran Jia, Xiangyu Qi, Jiachen T. Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
2023	J	`jnl`	Uncovering Adversarial Risks of Test-Time Adaptation. CoRR Tong Wu, Feiran Jia, Xiangyu Qi, Jiachen T. Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
2022	J	`jnl`	A Light Recipe to Train Robust Vision Transformers. CoRR Edoardo Debenedetti, Vikash Sehwag, Prateek Mittal
2022	J	`jnl`	DP-RAFT: A Differentially Private Recipe for Accelerated Fine-Tuning. CoRR Ashwinee Panda, Xinyu Tang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
2022	A*	`conf`	Generating High Fidelity Data from Low-density Regions using Diffusion Models. CVPR Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton-Ferrer
2022	J	`jnl`	Generating High Fidelity Data from Low-density Regions using Diffusion Models. CoRR Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton-Ferrer
2022	—	`conf`	Just Rotate it: Deploying Backdoor Attacks via Rotation Transformation. AISec@CCS Tong Wu, Tianhao Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
2022	J	`jnl`	Just Rotate it: Deploying Backdoor Attacks via Rotation Transformation. CoRR Tong Wu, Tianhao Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
2022	A*	`conf`	Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness? ICLR Vikash Sehwag, Saeed Mahloujifar, Tinashe Handina, Sihui Dai, Chong Xiang, Mung Chiang, Prateek Mittal
2022	A*	`conf`	Understanding Robust Learning through the Lens of Representation Similarities. NeurIPS Christian Cianfarani, Arjun Nitin Bhagoji, Vikash Sehwag, Ben Y. Zhao, Heather Zheng, Prateek Mittal
2022	J	`jnl`	Understanding Robust Learning through the Lens of Representation Similarities. CoRR Christian Cianfarani, Arjun Nitin Bhagoji, Vikash Sehwag, Ben Y. Zhao, Prateek Mittal
2021	—	`conf`	Beyond $L_{p}$ Norms: Delving Deeper into Robustness to Physical Image Transformations. MILCOM Vikash Sehwag, Jack W. Stokes, Cha Zhang
2021	J	`jnl`	Embedding delay-based physical unclonable functions in networks-on-chip. IET Circuits Devices Syst. Prasad Nagabhushanamgari, Vikash Sehwag, Indrajit Chakrabarti, Santanu Chattopadhyay
2021	J	`jnl`	Fast-Convergent Federated Learning. IEEE J. Sel. Areas Commun. Hung T. Nguyen, Vikash Sehwag, Seyyedali Hosseinalipour, Christopher G. Brinton, Mung Chiang, H. Vincent Poor
2021	J	`jnl`	Improving Adversarial Robustness Using Proxy Distributions. CoRR Vikash Sehwag, Saeed Mahloujifar, Tinashe Handina, Sihui Dai, Chong Xiang, Mung Chiang, Prateek Mittal
2021	A*	`conf`	Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries. ICML Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal
2021	J	`jnl`	Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries. CoRR Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal
2021	A*	`conf`	PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking. USENIX Security Symposium Chong Xiang, Arjun Nitin Bhagoji, Vikash Sehwag, Prateek Mittal
2021	—	`conf`	RobustBench: a standardized adversarial robustness benchmark. NeurIPS Datasets and Benchmarks Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Edoardo Debenedetti, Nicolas Flammarion, Mung Chiang, Prateek Mittal, Matthias Hein
2021	A*	`conf`	SSD: A Unified Framework for Self-Supervised Outlier Detection. ICLR Vikash Sehwag, Mung Chiang, Prateek Mittal
2021	J	`jnl`	SSD: A Unified Framework for Self-Supervised Outlier Detection. CoRR Vikash Sehwag, Mung Chiang, Prateek Mittal
2020	J	`jnl`	A Critical Evaluation of Open-World Machine Learning. CoRR Liwei Song, Vikash Sehwag, Arjun Nitin Bhagoji, Prateek Mittal
2020	J	`jnl`	Fast-Convergent Federated Learning. CoRR Hung T. Nguyen, Vikash Sehwag, Seyyedali Hosseinalipour, Christopher G. Brinton, Mung Chiang, H. Vincent Poor
2020	A*	`conf`	HYDRA: Pruning Adversarially Robust Neural Networks. NeurIPS Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana
2020	J	`jnl`	On Pruning Adversarially Robust Neural Networks. CoRR Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana
2020	J	`jnl`	PatchGuard: Provable Defense against Adversarial Patches Using Masks on Small Receptive Fields. CoRR Chong Xiang, Arjun Nitin Bhagoji, Vikash Sehwag, Prateek Mittal
2020	J	`jnl`	RobustBench: a standardized adversarial robustness benchmark. CoRR Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Nicolas Flammarion, Mung Chiang, Prateek Mittal, Matthias Hein
2020	J	`jnl`	Time for a Background Check! Uncovering the impact of Background Features on Deep Neural Networks. CoRR Vikash Sehwag, Rajvardhan Oak, Mung Chiang, Prateek Mittal
2019	—	`conf`	Analyzing the Robustness of Open-World Machine Learning. AISec@CCS Vikash Sehwag, Arjun Nitin Bhagoji, Liwei Song, Chawin Sitawarin, Daniel Cullina, Mung Chiang, Prateek Mittal
2019	J	`jnl`	Better the Devil you Know: An Analysis of Evasion Attacks using Out-of-Distribution Adversarial Examples. CoRR Vikash Sehwag, Arjun Nitin Bhagoji, Liwei Song, Chawin Sitawarin, Daniel Cullina, Mung Chiang, Prateek Mittal
2019	J	`jnl`	Towards Compact and Robust Deep Neural Networks. CoRR Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana
2018	J	`jnl`	A Parallel Stochastic Number Generator With Bit Permutation Networks. IEEE Trans. Circuits Syst. II Express Briefs Vikash Sehwag, N. Prasad, Indrajit Chakrabarti
2018	A*	`conf`	Not All Pixels are Born Equal: An Analysis of Evasion Attacks under Locality Constraints. CCS Vikash Sehwag, Chawin Sitawarin, Arjun Nitin Bhagoji, Arsalan Mosenia, Mung Chiang, Prateek Mittal
2016	J	`jnl`	TV-PUF : A Fast Lightweight Aging-Resistant Threshold Voltage PUF. IACR Cryptol. ePrint Arch. Tanujay Saha, Vikash Sehwag
2016	—	`conf`	TV-PUF: A Fast Lightweight Analog Physical Unclonable Function. iNIS Vikash Sehwag, Tanujay Saha
2016	—	`conf`	Variation Aware Performance Analysis of TFETs for Low-Voltage Computing. iNIS Vikash Sehwag, Saurav Maji, Mrigank Sharad
2015	J	`jnl`	Energy Efficient and High Performance Current-Mode Neural Network Circuit using Memristors and Digitally Assisted Analog CMOS Neurons. CoRR Aranya Goswamy, Sagar Kumashi, Vikash Sehwag, Siddharth Singh, Manny Jain, Kaushik Roy, Mrigank Sharad