FetchSGD: Communication-Efficient Federated Learning with Sketching. - Daniel Rothchild; Ashwinee Panda; Enayat Ullah; Nikita Ivkin; Ion Stoica; Vladimir Braverman; Joseph Gonzalez 001; Raman Arora (ICML, 2020)

SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification. - Ashwinee Panda; Saeed Mahloujifar; Arjun Nitin Bhagoji; Supriyo Chakraborty; Prateek Mittal (AISTATS, 2022)

Neurotoxin: Durable Backdoors in Federated Learning. - Zhengming Zhang 001; Ashwinee Panda; Linyue Song; Yaoqing Yang; Michael W. Mahoney; Prateek Mittal; Kannan Ramchandran; Joseph Gonzalez 001 (ICML, 2022)

DP-RAFT: A Differentially Private Recipe for Accelerated Fine-Tuning. - Ashwinee Panda; Xinyu Tang 003; Vikash Sehwag; Saeed Mahloujifar; Prateek Mittal (CoRR, 2022)

Differentially Private In-Context Learning. - Ashwinee Panda; Tong Wu; Jiachen T. Wang; Prateek Mittal (CoRR, 2023)

Visual Adversarial Examples Jailbreak Large Language Models. - Xiangyu Qi; Kaixuan Huang; Ashwinee Panda; Mengdi Wang; Prateek Mittal (CoRR, 2023)

Visual Adversarial Examples Jailbreak Aligned Large Language Models. - Xiangyu Qi; Kaixuan Huang; Ashwinee Panda; Peter Henderson 002; Mengdi Wang; Prateek Mittal (AAAI, 2024)

Dense Backpropagation Improves Routing for Sparsely-Gated Mixture-of-Experts. - Ashwinee Panda; Vatsal Baherwani; Zain Sarwar; Benjamin Thérien; Sambit Sahu; Stephen Rawls; Supriyo Chakraborty; Tom Goldstein (ENLSP, 2024)

StructMoE: Structured Mixture of Experts Using Low Rank Experts. - Zain Sarwar; Ashwinee Panda; Benjamin Thérien; Stephen Rawls; Anirban Das; Kartik Balasubramaniam; Berkcan Kapusuzoglu; Shixiong Zhang; Sambit Sahu; Milind Naphade; Supriyo Chakraborty (ENLSP, 2024)

Teach LLMs to Phish: Stealing Private Information from Language Models. - Ashwinee Panda; Christopher A. Choquette-Choo; Zhengming Zhang 001; Yaoqing Yang; Prateek Mittal (ICLR, 2024)

Privacy-Preserving In-Context Learning for Large Language Models. - Tong Wu; Ashwinee Panda; Jiachen T. Wang; Prateek Mittal (ICLR, 2024)

A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization. - Ashwinee Panda; Xinyu Tang 003; Saeed Mahloujifar; Vikash Sehwag; Prateek Mittal (ICML, 2024)

Lottery Ticket Adaptation: Mitigating Destructive Interference in LLMs. - Ashwinee Panda; Berivan Isik; Xiangyu Qi; Sanmi Koyejo; Tsachy Weissman; Prateek Mittal (CoRR, 2024)

Refusal Tokens: A Simple Way to Calibrate Refusals in Large Language Models. - Neel Jain; Aditya Shrivastava; Chen Zhu 001; Daben Liu; Alfy Samuel; Ashwinee Panda; Anoop Kumar; Micah Goldblum; Tom Goldstein (CoRR, 2024)

Privacy Auditing of Large Language Models. - Ashwinee Panda; Xinyu Tang 003; Christopher A. Choquette-Choo; Milad Nasr; Prateek Mittal (ICLR, 2025)

Safety Alignment Should be Made More Than Just a Few Tokens Deep. - Xiangyu Qi; Ashwinee Panda; Kaifeng Lyu; Xiao Ma 010; Subhrajit Roy; Ahmad Beirami; Prateek Mittal; Peter Henderson 002 (ICLR, 2025)

Differentially Private Image Classification by Learning Priors from Random Processes. - Xinyu Tang 003; Ashwinee Panda; Vikash Sehwag; Prateek Mittal (J. Priv. Confidentiality, 2025)

Private Fine-tuning of Large Language Models with Zeroth-order Optimization. - Xinyu Tang 003; Ashwinee Panda; Milad Nasr; Saeed Mahloujifar; Prateek Mittal (Trans. Mach. Learn. Res., 2025)

Gemstones: A Model Suite for Multi-Faceted Scaling Laws. - Sean McLeish; John Kirchenbauer; David Yu Miller; Siddharth Singh; Abhinav Bhatele; Micah Goldblum; Ashwinee Panda; Tom Goldstein (CoRR, 2025)

Continual Pre-training of MoEs: How robust is your router? - Benjamin Thérien; Charles-Étienne Joseph; Zain Sarwar; Ashwinee Panda; Anirban Das; Shi-Xiong Zhang 001; Stephen Rawls; Sambit Sahu; Eugene Belilovsky; Irina Rish (CoRR, 2025)

Using Attention Sinks to Identify and Evaluate Dormant Heads in Pretrained LLMs. - Pedro Sandoval Segura; Xijun Wang; Ashwinee Panda; Micah Goldblum; Ronen Basri; Tom Goldstein; David Jacobs 001 (CoRR, 2025)

LoRI: Reducing Cross-Task Interference in Multi-Task Low-Rank Adaptation. - Juzheng Zhang; Jiacheng You; Ashwinee Panda; Tom Goldstein (CoRR, 2025)

Analysis of Attention in Video Diffusion Transformers. - Yuxin Wen; Jim Wu; Ajay Jain; Tom Goldstein; Ashwinee Panda (CoRR, 2025)

Dense Backpropagation Improves Training for Sparse Mixture-of-Experts. - Ashwinee Panda; Vatsal Baherwani; Zain Sarwar; Benjamin Thérien; Supriyo Chakraborty; Tom Goldstein (CoRR, 2025)