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From Prompts to Posteriors: Can LLM Agents Perform Bayesian Inference in Context?
Large language models (LLMs) are increasingly applied across the scientific discovery pipeline, from synthesizing literature to generating hypotheses to informing experimental design. A unifying principle behind these tasks is the need to continuously update beliefs as evidence accumulates, for whic
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