Varun Chandrasekaran

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 50

Top Topics

Machine Learning

Constraint Satisfaction

General Intelligence

Top Venues

IEEE Symposium on Security and Privacy

Publications

Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yüksekgönül, Rahee Ghosh Peshawaria, Ranjita Naik, Besmira Nushi
KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval. ICLR (2024)
Erik Jones, Hamid Palangi, Clarisse Simões, Varun Chandrasekaran, Subhabrata Mukherjee, Arindam Mitra, Ahmed Hassan Awadallah, Ece Kamar
Teaching Language Models to Hallucinate Less with Synthetic Tasks. ICLR (2024)
Qilong Wu, Varun Chandrasekaran
Bypassing LLM Watermarks with Color-Aware Substitutions. ACL (1) (2024)
Mert Yüksekgönül, Varun Chandrasekaran, Erik Jones, Suriya Gunasekar, Ranjita Naik, Hamid Palangi, Ece Kamar, Besmira Nushi
Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models. ICLR (2024)
Rishabh Adiga, Lakshmi Subramanian, Varun Chandrasekaran
Designing Informative Metrics for Few-Shot Example Selection. ACL (Findings) (2024)
Fan Wu, Huseyin A. Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan Kulkarni, Robert Sim
Privately Aligning Language Models with Reinforcement Learning. ICLR (2024)
Rishabh Adiga, Lakshminarayanan Subramanian, Varun Chandrasekaran
Designing Informative Metrics for Few-Shot Example Selection. CoRR (2024)
Fan Wu, Emily Black, Varun Chandrasekaran
Generative Monoculture in Large Language Models. CoRR (2024)
Qilong Wu, Varun Chandrasekaran
Bypassing LLM Watermarks with Color-Aware Substitutions. CoRR (2024)
Mert Yüksekgönül, Varun Chandrasekaran, Erik Jones, Suriya Gunasekar, Ranjita Naik, Hamid Palangi, Ece Kamar, Besmira Nushi
Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models. CoRR (2023)
Fan Wu, Huseyin A. Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan Kulkarni, Robert Sim
Privately Aligning Language Models with Reinforcement Learning. CoRR (2023)
Ranjita Naik, Varun Chandrasekaran, Mert Yüksekgönül, Hamid Palangi, Besmira Nushi
Diversity of Thought Improves Reasoning Abilities of Large Language Models. CoRR (2023)
Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yüksekgönül, Rahee Ghosh Peshawaria, Ranjita Naik, Besmira Nushi
KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval. CoRR (2023)
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
Sparks of Artificial General Intelligence: Early experiments with GPT-4. CoRR (2023)
Jihye Choi, Shruti Tople, Varun Chandrasekaran, Somesh Jha
Why Train More? Effective and Efficient Membership Inference via Memorization. CoRR (2023)
Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot
Proof-of-Learning is Currently More Broken Than You Think. EuroS&P (2023)
Erik Jones, Hamid Palangi, Clarisse Simões, Varun Chandrasekaran, Subhabrata Mukherjee, Arindam Mitra, Ahmed Hassan Awadallah, Ece Kamar
Teaching Language Models to Hallucinate Less with Synthetic Tasks. CoRR (2023)
Tejumade Afonja, Lucas Bourtoule, Varun Chandrasekaran, Sageev Oore, Nicolas Papernot
Generative Extraction of Audio Classifiers for Speaker Identification. CoRR (2022)
Brian Tang, Dakota Sullivan, Bengisu Cagiltay, Varun Chandrasekaran, Kassem Fawaz, Bilge Mutlu
CONFIDANT: A Privacy Controller for Social Robots. CoRR (2022)
Thorsten Eisenhofer, Doreen Riepel, Varun Chandrasekaran, Esha Ghosh, Olga Ohrimenko, Nicolas Papernot
Verifiable and Provably Secure Machine Unlearning. CoRR (2022)
Anvith Thudi, Gabriel Deza, Varun Chandrasekaran, Nicolas Papernot
Unrolling SGD: Understanding Factors Influencing Machine Unlearning. EuroS&P (2022)
Varun Chandrasekaran, Suman Banerjee, Diego Perino, Nicolas Kourtellis
Hierarchical Federated Learning with Privacy. CoRR (2022)
Brian Tang, Dakota Sullivan, Bengisu Cagiltay, Varun Chandrasekaran, Kassem Fawaz, Bilge Mutlu
CONFIDANT: A Privacy Controller for Social Robots. HRI (2022)
Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot
On the Fundamental Limits of Formally (Dis)Proving Robustness in Proof-of-Learning. CoRR (2022)
Hui Xu, Guanpeng Li, Homa Alemzadeh, Rakesh Bobba, Varun Chandrasekaran, David E. Evans, Nicolas Papernot, Karthik Pattabiraman, Florian Tramèr
Fourth International Workshop on Dependable and Secure Machine Learning - DSML 2021. DSN Workshops (2021)
Anvith Thudi, Gabriel Deza, Varun Chandrasekaran, Nicolas Papernot
Unrolling SGD: Understanding Factors Influencing Machine Unlearning. CoRR (2021)
Adelin Travers, Lorna Licollari, Guanghan Wang, Varun Chandrasekaran, Adam Dziedzic, David Lie, Nicolas Papernot
On the Exploitability of Audio Machine Learning Pipelines to Surreptitious Adversarial Examples. CoRR (2021)
Varun Chandrasekaran, Suman Banerjee, Bilge Mutlu, Kassem Fawaz
PowerCut and Obfuscator: An Exploration of the Design Space for Privacy-Preserving Interventions for Smart Speakers. SOUPS @ USENIX Security Symposium (2021)
Lucas Bourtoule, Varun Chandrasekaran, Christopher A. Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, Nicolas Papernot
Machine Unlearning. IEEE Symposium on Security and Privacy (2021)
Hengrui Jia, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Anvith Thudi, Varun Chandrasekaran, Nicolas Papernot
Proof-of-Learning: Definitions and Practice. CoRR (2021)
Varun Chandrasekaran, Hengrui Jia, Anvith Thudi, Adelin Travers, Mohammad Yaghini, Nicolas Papernot
SoK: Machine Learning Governance. CoRR (2021)
Hengrui Jia, Christopher A. Choquette-Choo, Varun Chandrasekaran, Nicolas Papernot
Entangled Watermarks as a Defense against Model Extraction. USENIX Security Symposium (2021)
Hengrui Jia, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Anvith Thudi, Varun Chandrasekaran, Nicolas Papernot
Proof-of-Learning: Definitions and Practice. IEEE Symposium on Security and Privacy (2021)
Varun Chandrasekaran, Chuhan Gao, Brian Tang, Kassem Fawaz, Somesh Jha, Suman Banerjee
Face-Off: Adversarial Face Obfuscation. Proc. Priv. Enhancing Technol. 2021 (2) (2021)
Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople
Causally Constrained Data Synthesis for Private Data Release. CoRR (2021)
Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
A General Framework For Detecting Anomalous Inputs to DNN Classifiers. ICML (2021)
Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
Detecting Anomalous Inputs to DNN Classifiers By Joint Statistical Testing at the Layers. CoRR (2020)
Homa Alemzadeh, Rakesh Bobba, Varun Chandrasekaran, David E. Evans, Nicolas Papernot, Karthik Pattabiraman, Florian Tramèr
Third International Workshop on Dependable and Secure Machine Learning - DSML 2020. DSN Workshops (2020)
Sanghyun Hong, Varun Chandrasekaran, Yigitcan Kaya, Tudor Dumitras, Nicolas Papernot
On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping. CoRR (2020)
Varun Chandrasekaran, Kamalika Chaudhuri, Irene Giacomelli, Somesh Jha, Songbai Yan
Exploring Connections Between Active Learning and Model Extraction. USENIX Security Symposium (2020)
Chuhan Gao, Varun Chandrasekaran, Kassem Fawaz, Somesh Jha
Face-Off: Adversarial Face Obfuscation. CoRR (2020)
Lucas Bourtoule, Varun Chandrasekaran, Christopher A. Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, Nicolas Papernot
Machine Unlearning. CoRR (2019)
Yijing Zeng, Varun Chandrasekaran, Suman Banerjee, Domenico Giustiniano
A Framework for Analyzing Spectrum Characteristics in Large Spatio-temporal Scales. MobiCom (2019)
Varun Chandrasekaran, Brian Tang, Varsha Pendyala, Kassem Fawaz, Somesh Jha, Xi Wu
Enhancing ML Robustness Using Physical-World Constraints. CoRR (2019)
Lakshya Jain, Wilson Wu, Steven Chen, Uyeong Jang, Varun Chandrasekaran, Sanjit A. Seshia, Somesh Jha
Generating Semantic Adversarial Examples with Differentiable Rendering. CoRR (2019)
Varun Chandrasekaran, Kamalika Chaudhuri, Irene Giacomelli, Somesh Jha, Songbai Yan
Model Extraction and Active Learning. CoRR (2018)
Chuhan Gao, Varun Chandrasekaran, Kassem Fawaz, Suman Banerjee
Traversing the Quagmire that is Privacy in your Smart Home. IoT S&P@SIGCOMM (2018)
Varun Chandrasekaran, Kassem Fawaz, Bilge Mutlu, Suman Banerjee
Characterizing Privacy Perceptions of Voice Assistants: A Technology Probe Study. CoRR (2018)
Varun Chandrasekaran, Fareeha Amjad, Ashlesh Sharma, Lakshminarayanan Subramanian
Secure Mobile Identities. CoRR (2016)
Ashlesh Sharma, Varun Chandrasekaran, Fareeha Amjad, Dennis E. Shasha, Lakshminarayanan Subramanian
Alphacodes: Usable, Secure Transactions with Untrusted Providers using Human Computable Puzzles. ACM DEV (2016)