Large Discovery Models: Empirically-grounded Model-Based Open-Ended Search
This work introduces the Large Discovery Model (LDM), an empirically grounded recurrent architecture that couples a generative model with a Bayesian non-parametric reward surrogate model, yielding an uncertainty-aware value that guides candidate generation, refinement, and selection.
Zhongwei Yu, Yan Song, Xue Yan et al.
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