4 citations · 15 across the 14 of their papers we have counts for
3 papers · 1 filter
Elijah: Eliminating Backdoors Injected in Diffusion Models via Distribution Shift
Shengwei An, Sheng-Yen Chou, Kaiyuan Zhang +8
Diffusion models (DM) have become state-of-the-art generative models because of their capability to generate high-quality images from noises without adversarial training. However,…
NeuralFuse: Learning to Recover the Accuracy of Access-Limited Neural Network Inference in Low-Voltage Regimes
Hao-Lun Sun, Lei Hsiung, Nandhini Chandramoorthy +2
Deep neural networks (DNNs) have become ubiquitous in machine learning, but their energy consumption remains problematically high. An effective strategy for reducing such consumpti…
Uncovering and Quantifying Social Biases in Code Generation
Yan Liu, Xiaokang Chen, Yan Gao +6
With the popularity of automatic code generation tools, such as Copilot, the study of the potential hazards of these tools is gaining importance. In this work, we explore the socia…