no code implementations • 3 Apr 2024 • Rishub Tamirisa, Chulin Xie, Wenxuan Bao, Andy Zhou, Ron Arel, Aviv Shamsian
Recent methods addressed the client data heterogeneity issue via personalized federated learning (PFL) - a class of FL algorithms aiming to personalize learned global knowledge to better suit the clients' local data distributions.
no code implementations • 5 Feb 2024 • Haibo Jin, Ruoxi Chen, Andy Zhou, Jinyin Chen, Yang Zhang, Haohan Wang
Our system of different roles will leverage this knowledge graph to generate new jailbreaks, which have proved effective in inducing LLMs to generate unethical or guideline-violating responses.
1 code implementation • 30 Jan 2024 • Andy Zhou, Bo Li, Haohan Wang
Despite advances in AI alignment, language models (LM) remain vulnerable to adversarial attacks or jailbreaking, in which adversaries modify input prompts to induce harmful behavior.
1 code implementation • NeurIPS 2023 • Andy Zhou, Jindong Wang, Yu-Xiong Wang, Haohan Wang
We propose a conceptually simple and lightweight framework for improving the robustness of vision models through the combination of knowledge distillation and data augmentation.
Ranked #13 on Domain Generalization on ImageNet-Sketch
1 code implementation • 6 Oct 2023 • Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, Yu-Xiong Wang
While large language models (LLMs) have demonstrated impressive performance on a range of decision-making tasks, they rely on simple acting processes and fall short of broad deployment as autonomous agents.
Ranked #3 on Code Generation on HumanEval
1 code implementation • ICCV 2023 • Zeyi Huang, Andy Zhou, Zijian Lin, Mu Cai, Haohan Wang, Yong Jae Lee
Domain generalization studies the problem of training a model with samples from several domains (or distributions) and then testing the model with samples from a new, unseen domain.
Ranked #15 on Domain Generalization on PACS
no code implementations • 23 Jun 2023 • Rishub Tamirisa, John Won, Chengjun Lu, Ron Arel, Andy Zhou
Recent advancements in federated learning (FL) seek to increase client-level performance by fine-tuning client parameters on local data or personalizing architectures for the local task.
no code implementations • 9 Mar 2021 • Andy Zhou, Rikky Muller, Jan Rabaey
Electromyogram (EMG) pattern recognition can be used to classify hand gestures and movements for human-machine interface and prosthetics applications, but it often faces reliability issues resulting from limb position change.
no code implementations • 2 Jan 2019 • Ali Moin, Andy Zhou, Simone Benatti, Abbas Rahimi, Luca Benini, Jan M. Rabaey
Varying contraction levels of muscles is a big challenge in electromyography-based gesture recognition.
1 code implementation • 28 Feb 2018 • Ali Moin, Andy Zhou, Abbas Rahimi, Simone Benatti, Alisha Menon, Senam Tamakloe, Jonathan Ting, Natasha Yamamoto, Yasser Khan, Fred Burghardt, Luca Benini, Ana C. Arias, Jan M. Rabaey
We present an end-to-end system combating this variability using a large-area, high-density sensor array and a robust classification algorithm.