Task Inference Beyond Least Squares in Behavioral Foundation Models
Behavioral Foundation Models (BFMs) aim to solve a wide range of downstream tasks without test-time policy learning by inferring a task vector from the reward function. While efficient, the retrieved policies are often suboptimal because of how this task vector is inferred, typically with ordinary least squares (OLS)....
Kuan-Hsun Tu, Chi-Hsun Chiang, Hsin-Wei Chen et al.
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