Garg, Siddharth

23 publications

TMLR 2025 EMMA: Efficient Visual Alignment in Multi-Modal LLMs Sara Ghazanfari, Alexandre Araujo, Prashanth Krishnamurthy, Siddharth Garg, Farshad Khorrami

NeurIPS 2025 VeriLoC: Line-of-Code Level Prediction of Hardware Design Quality from Verilog Code Raghu Vamshi Hemadri, Jitendra Bhandari, Andre Nakkab, Johann Knechtel, Badri P Gopalan, Ramesh Narayanaswamy, Ramesh Karri, Siddharth Garg

NeurIPS 2025 VeriThoughts: Enabling Automated Verilog Code Generation Using Reasoning and Formal Verification Patrick Yubeaton, Andre Nakkab, Weihua Xiao, Luca Collini, Ramesh Karri, Chinmay Hegde, Siddharth Garg

TMLR 2024 Hyper-Parameter Tuning for Fair Classification Without Sensitive Attribute Access Akshaj Kumar Veldanda, Ivan Brugere, Sanghamitra Dutta, Alan Mishler, Siddharth Garg

ICLR 2024 LipSim: A Provably Robust Perceptual Similarity Metric Sara Ghazanfari, Alexandre Araujo, Prashanth Krishnamurthy, Farshad Khorrami, Siddharth Garg

NeurIPS 2024 NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security Minghao Shao, Sofija Jancheska, Meet Udeshi, Brendan Dolan-Gavitt, Haoran Xi, Kimberly Milner, Boyuan Chen, Max Yin, Siddharth Garg, Prashanth Krishnamurthy, Farshad Khorrami, Ramesh Karri, Muhammad Shafique

ICLR 2024 Novel Quadratic Constraints for Extending LipSDP Beyond Slope-Restricted Activations Patricia Pauli, Aaron J Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Frank Allgöwer, Bin Hu

AISTATS 2024 On the (In)feasibility of ML Backdoor Detection as an Hypothesis Testing Problem Georg Pichler, Marco Romanelli, Divya Prakash Manivannan, Prashanth Krishnamurthy, Farshad Khorrami, Siddharth Garg

TMLR 2024 PriViT: Vision Transformers for Private Inference Naren Dhyani, Jianqiao Cambridge Mo, Patrick Yubeaton, Minsu Cho, Ameya Joshi, Siddharth Garg, Brandon Reagen, Chinmay Hegde

ICLR 2024 Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization Animesh Basak Chowdhury, Marco Romanelli, Benjamin Tan, Ramesh Karri, Siddharth Garg

NeurIPS 2023 Exploiting Connections Between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models Aaron Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Bin Hu

TMLR 2023 Fairness via In-Processing in the Over-Parameterized Regime: A Cautionary Tale with MinDiff Loss Akshaj Kumar Veldanda, Ivan Brugere, Jiahao Chen, Sanghamitra Dutta, Alan Mishler, Siddharth Garg

NeurIPSW 2023 Investigating Hiring Bias in Large Language Models Akshaj Kumar Veldanda, Fabian Grob, Shailja Thakur, Hammond Pearce, Benjamin Tan, Ramesh Karri, Siddharth Garg

NeurIPSW 2023 On the Limitation of Backdoor Detection Methods Georg Pichler, Marco Romanelli, Divya Prakash Manivannan, Prashanth Krishnamurthy, Farshad Khorrami, Siddharth Garg

ICMLW 2023 R-LPIPS: An Adversarially Robust Perceptual Similarity Metric Sara Ghazanfari, Siddharth Garg, Prashanth Krishnamurthy, Farshad Khorrami, Alexandre Araujo

UAI 2023 Towards Better Certified Segmentation via Diffusion Models Othmane Laousy, Alexandre Araujo, Guillaume Chassagnon, Marie-Pierre Revel, Siddharth Garg, Farshad Khorrami, Maria Vakalopoulou

ICML 2022 Selective Network Linearization for Efficient Private Inference Minsu Cho, Ameya Joshi, Brandon Reagen, Siddharth Garg, Chinmay Hegde

ICMLW 2021 Adversarially Robust Learning via Entropic Regularization Gauri Jagatap, Ameya Joshi, Animesh Basak Chowdhury, Siddharth Garg, Chinmay Hegde

NeurIPS 2021 Circa: Stochastic ReLUs for Private Deep Learning Zahra Ghodsi, Nandan Kumar Jha, Brandon Reagen, Siddharth Garg

ICML 2021 DeepReDuce: ReLU Reduction for Fast Private Inference Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen

AAAI 2021 Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images Kang Liu, Benjamin Tan, Siddharth Garg

NeurIPS 2020 CryptoNAS: Private Inference on a ReLU Budget Zahra Ghodsi, Akshaj Kumar Veldanda, Brandon Reagen, Siddharth Garg

NeurIPS 2017 SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud Zahra Ghodsi, Tianyu Gu, Siddharth Garg