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Amortizing Sequential Experimental Design in Reasoning LLMs

arXiv:2610.20832v1 Announce Type: new Abstract: 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…

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  1. 2026-10-16 04:00 · arXiv cs.LG
    Amortizing Sequential Experimental Design in Reasoning LLMs

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