Chiang, Ping-Yeh

8 publications

ICLR 2024 NEFTune: Noisy Embeddings Improve Instruction Finetuning Neel Jain, Ping-yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein

ICLR 2023 Loss Landscapes Are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent Ping-yeh Chiang, Renkun Ni, David Yu Miller, Arpit Bansal, Jonas Geiping, Micah Goldblum, Tom Goldstein

ICML 2022 Certified Neural Network Watermarks with Randomized Smoothing Arpit Bansal, Ping-Yeh Chiang, Michael J Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P Dickerson, Tom Goldstein

NeurIPS 2021 Adversarial Examples Make Strong Poisons Liam Fowl, Micah Goldblum, Ping-yeh Chiang, Jonas Geiping, Wojciech Czaja, Tom Goldstein

ICLR 2021 WrapNet: Neural Net Inference with Ultra-Low-Precision Arithmetic Renkun Ni, Hong-min Chu, Oscar Castaneda, Ping-yeh Chiang, Christoph Studer, Tom Goldstein

ICLR 2020 Certified Defenses for Adversarial Patches Ping-Yeh Chiang, Renkun Ni, Ahmed Abdelkader, Chen Zhu, Christoph Studor, Tom Goldstein

NeurIPS 2020 Certifying Strategyproof Auction Networks Michael Curry, Ping-yeh Chiang, Tom Goldstein, John Dickerson

NeurIPS 2020 Detection as Regression: Certified Object Detection with Median Smoothing Ping-yeh Chiang, Michael Curry, Ahmed Abdelkader, Aounon Kumar, John Dickerson, Tom Goldstein