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cs.LG2024
UDA-Bench: Revisiting Common Assumptions in Unsupervised Domain Adaptation Using a Standardized Framework
Tarun Kalluri, Sreyas Ravichandran, Manmohan Chandraker
In this work, we take a deeper look into the diverse factors that influence the efficacy of modern unsupervised domain adaptation (UDA) methods using a large-scale, controlled empi…
cs.LG2024
A Minimalist Prompt for Zero-Shot Policy Learning
Meng Song, Xuezhi Wang, Tanay Biradar +2
Transformer-based methods have exhibited significant generalization ability when prompted with target-domain demonstrations or example solutions during inference. Although demonstr…