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Large Discovery Models: Empirically-grounded Model-Based Open-Ended Search

57 upvotes · 16 AUG 2026 · Zhongwei Yu, Yan Song, Xue Yan et al.

This paper develops a new AI model that can efficiently search through vast spaces of possibilities, such as designing molecules or optimizing neural networks, by combining a generative model with a model that estimates the potential performance of each candidate. Practitioners might care about this approach because it can significantly speed up the discovery process and improve the quality of the results.

generative modelsBayesian non-parametric reward modelsopen-ended hypothesis spacesmolecular optimisationcontinual learning