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Large Discovery Models: learning where to search next An LLM proposes, a Bayesian surrogate scores uncertainty, and the loop iterates — cutting validation error by 2.4x, binding energy by 18%, and boosting molecular objectives by 60%+ across programs, proteins, and molecules. https://t.co/AW0Dj4vIXX
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