Author

Anita Kriz

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#artificial intelligence Preprint Oct 2026

Amortizing Sequential Experimental Design in Reasoning LLMs

Despite their extensive pretraining knowledge and strong reasoning capabilities, large language models (LLMs) struggle to adaptively gather information in experimental design tasks. We study how to amortize sequential Bayesian experimental design (BED) into an LLM by explicitly training the reasoning that guides action...

Anita Kriz, Antonin Berthon, Nicolás Astorga et al. · 0 citations