Varun Chandrasekaran

According to our database, Varun Chandrasekaran authored at least 44 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

BENCHAGENTS: Automated Benchmark Creation with Agent Interaction.

Natasha Butt, Varun Chandrasekaran, Neel Joshi, Besmira Nushi, Vidhisha Balachandran

CoRR, 2024

Attention Speaks Volumes: Localizing and Mitigating Bias in Language Models.

Rishabh Adiga, Besmira Nushi, Varun Chandrasekaran

CoRR, 2024

Unearthing Skill-Level Insights for Understanding Trade-Offs of Foundation Models.

Mazda Moayeri, Vidhisha Balachandran, Varun Chandrasekaran, Safoora Yousefi, Thomas Fel, Soheil Feizi, Besmira Nushi, Neel Joshi, Vibhav Vineet

CoRR, 2024

LOTOS: Layer-wise Orthogonalization for Training Robust Ensembles.

Ali Ebrahimpour Boroojeny, Hari Sundaram, Varun Chandrasekaran

CoRR, 2024

Generative Monoculture in Large Language Models.

Fan Wu, Emily Black, Varun Chandrasekaran

CoRR, 2024

Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models.

Mert Yüksekgönül, Varun Chandrasekaran, Erik Jones, Suriya Gunasekar, Ranjita Naik, Hamid Palangi, Ece Kamar, Besmira Nushi

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Privately Aligning Language Models with Reinforcement Learning.

Fan Wu, Huseyin A. Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan Kulkarni, Robert Sim

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Teaching Language Models to Hallucinate Less with Synthetic Tasks.

Erik Jones, Hamid Palangi, Clarisse Simões, Varun Chandrasekaran, Subhabrata Mukherjee, Arindam Mitra, Ahmed Hassan Awadallah, Ece Kamar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval.

Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yüksekgönül, Rahee Ghosh Peshawaria, Ranjita Naik, Besmira Nushi

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Designing Informative Metrics for Few-Shot Example Selection.

Rishabh Adiga, Lakshmi Subramanian, Varun Chandrasekaran

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Bypassing LLM Watermarks with Color-Aware Substitutions.

Qilong Wu, Varun Chandrasekaran

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Why Train More? Effective and Efficient Membership Inference via Memorization.

Jihye Choi, Shruti Tople, Varun Chandrasekaran, Somesh Jha

CoRR, 2023

Diversity of Thought Improves Reasoning Abilities of Large Language Models.

Ranjita Naik, Varun Chandrasekaran, Mert Yüksekgönül, Hamid Palangi, Besmira Nushi

CoRR, 2023

Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott M. Lundberg, Harsha Nori, Hamid Palangi, Marco Túlio Ribeiro, Yi Zhang

CoRR, 2023

Proof-of-Learning is Currently More Broken Than You Think.

Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot

Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023

2022

Verifiable and Provably Secure Machine Unlearning.

Thorsten Eisenhofer, Doreen Riepel, Varun Chandrasekaran, Esha Ghosh, Olga Ohrimenko, Nicolas Papernot

CoRR, 2022

On the Fundamental Limits of Formally (Dis)Proving Robustness in Proof-of-Learning.

Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot

CoRR, 2022

Generative Extraction of Audio Classifiers for Speaker Identification.

Tejumade Afonja, Lucas Bourtoule, Varun Chandrasekaran, Sageev Oore, Nicolas Papernot

CoRR, 2022

Hierarchical Federated Learning with Privacy.

Varun Chandrasekaran, Suman Banerjee, Diego Perino, Nicolas Kourtellis

CoRR, 2022

CONFIDANT: A Privacy Controller for Social Robots.

Brian Tang, Dakota Sullivan, Bengisu Cagiltay, Varun Chandrasekaran, Kassem Fawaz, Bilge Mutlu

Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction, 2022

Unrolling SGD: Understanding Factors Influencing Machine Unlearning.

Anvith Thudi, Gabriel Deza, Varun Chandrasekaran, Nicolas Papernot

Proceedings of the 7th IEEE European Symposium on Security and Privacy, 2022

2021

Face-Off: Adversarial Face Obfuscation.

Varun Chandrasekaran, Chuhan Gao, Brian Tang, Kassem Fawaz, Somesh Jha, Suman Banerjee

Proc. Priv. Enhancing Technol., 2021

SoK: Machine Learning Governance.

Varun Chandrasekaran, Hengrui Jia, Anvith Thudi, Adelin Travers, Mohammad Yaghini, Nicolas Papernot

CoRR, 2021

On the Exploitability of Audio Machine Learning Pipelines to Surreptitious Adversarial Examples.

Adelin Travers, Lorna Licollari, Guanghan Wang, Varun Chandrasekaran, Adam Dziedzic, David Lie, Nicolas Papernot

CoRR, 2021

Causally Constrained Data Synthesis for Private Data Release.

Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople

CoRR, 2021

Entangled Watermarks as a Defense against Model Extraction.

Hengrui Jia, Christopher A. Choquette-Choo, Varun Chandrasekaran, Nicolas Papernot

Proceedings of the 30th USENIX Security Symposium, 2021

Proof-of-Learning: Definitions and Practice.

Hengrui Jia, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Anvith Thudi, Varun Chandrasekaran, Nicolas Papernot

Proceedings of the 42nd IEEE Symposium on Security and Privacy, 2021

Machine Unlearning.

Lucas Bourtoule, Varun Chandrasekaran, Christopher A. Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, Nicolas Papernot

Proceedings of the 42nd IEEE Symposium on Security and Privacy, 2021

PowerCut and Obfuscator: An Exploration of the Design Space for Privacy-Preserving Interventions for Smart Speakers.

Varun Chandrasekaran, Suman Banerjee, Bilge Mutlu, Kassem Fawaz

Proceedings of the Seventeenth Symposium on Usable Privacy and Security, 2021

A General Framework For Detecting Anomalous Inputs to DNN Classifiers.

Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee

Proceedings of the 38th International Conference on Machine Learning, 2021

Fourth International Workshop on Dependable and Secure Machine Learning - DSML 2021.

Hui Xu, Guanpeng Li, Homa Alemzadeh, Rakesh Bobba, Varun Chandrasekaran, David E. Evans, Nicolas Papernot, Karthik Pattabiraman, Florian Tramèr

Proceedings of the 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2021

2020

Detecting Anomalous Inputs to DNN Classifiers By Joint Statistical Testing at the Layers.

Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee

CoRR, 2020

Face-Off: Adversarial Face Obfuscation.

Chuhan Gao, Varun Chandrasekaran, Kassem Fawaz, Somesh Jha

CoRR, 2020

On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping.

Sanghyun Hong, Varun Chandrasekaran, Yigitcan Kaya, Tudor Dumitras, Nicolas Papernot

CoRR, 2020

Exploring Connections Between Active Learning and Model Extraction.

Varun Chandrasekaran, Kamalika Chaudhuri, Irene Giacomelli, Somesh Jha, Songbai Yan

Proceedings of the 29th USENIX Security Symposium, 2020

Third International Workshop on Dependable and Secure Machine Learning - DSML 2020.

Homa Alemzadeh, Rakesh Bobba, Varun Chandrasekaran, David E. Evans, Nicolas Papernot, Karthik Pattabiraman, Florian Tramèr

Proceedings of the 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2020

2019

Generating Semantic Adversarial Examples with Differentiable Rendering.

Lakshya Jain, Wilson Wu, Steven Chen, Uyeong Jang, Varun Chandrasekaran, Sanjit A. Seshia, Somesh Jha

CoRR, 2019

Enhancing ML Robustness Using Physical-World Constraints.

Varun Chandrasekaran, Brian Tang, Varsha Pendyala, Kassem Fawaz, Somesh Jha, Xi Wu

CoRR, 2019

A Framework for Analyzing Spectrum Characteristics in Large Spatio-temporal Scales.

Yijing Zeng, Varun Chandrasekaran, Suman Banerjee, Domenico Giustiniano

Proceedings of the 25th Annual International Conference on Mobile Computing and Networking, 2019

2018

Characterizing Privacy Perceptions of Voice Assistants: A Technology Probe Study.

Varun Chandrasekaran, Kassem Fawaz, Bilge Mutlu, Suman Banerjee

CoRR, 2018

Model Extraction and Active Learning.

Varun Chandrasekaran, Kamalika Chaudhuri, Irene Giacomelli, Somesh Jha, Songbai Yan

CoRR, 2018

Traversing the Quagmire that is Privacy in your Smart Home.

Chuhan Gao, Varun Chandrasekaran, Kassem Fawaz, Suman Banerjee

Proceedings of the 2018 Workshop on IoT Security and Privacy, 2018

2016

Secure Mobile Identities.

Varun Chandrasekaran, Fareeha Amjad, Ashlesh Sharma, Lakshminarayanan Subramanian

CoRR, 2016

Alphacodes: Usable, Secure Transactions with Untrusted Providers using Human Computable Puzzles.

Ashlesh Sharma, Varun Chandrasekaran, Fareeha Amjad, Dennis E. Shasha, Lakshminarayanan Subramanian

Proceedings of the 7th Annual Symposium on Computing for Development, 2016