AI RESEARCH
A Flow Matching Algorithm for Many-Shot Adaptation to Unseen Distributions
arXiv CS.LG
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ArXi:2605.06272v1 Announce Type: new While generative modeling has achieved remarkable success on tasks like natural language-conditioned image generation, enabling model adaptation from example data points remains a relatively underexplored and challenging problem. To this end, we propose Function Projection for Flow Matching (FP-FM), an algorithm that directly conditions generation on samples from the target distribution. FP-FM learns basis functions to span the velocity fields corresponding to a set of.