10 citations · 32 across the 14 of their papers we have counts for
4 papers · 1 filter
Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models
Andy Zhou, Jindong Wang, Yu-Xiong Wang +1
We propose a conceptually simple and lightweight framework for improving the robustness of vision models through the combination of knowledge distillation and data augmentation. We…
Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models
Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman +2
While language models (LMs) have shown potential across a range of decision-making tasks, their reliance on simple acting processes limits their broad deployment as autonomous agen…
A Sentence Speaks a Thousand Images: Domain Generalization through Distilling CLIP with Language Guidance
Zeyi Huang, Andy Zhou, Zijian Lin +3
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…
FedSelect: Customized Selection of Parameters for Fine-Tuning during Personalized Federated Learning
Rishub Tamirisa, John Won, Chengjun Lu +2
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…