AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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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...
This work proposes ACTMED (Adaptive Clinical Test selection via Model-based Experimental Design), a diagnostic framework that integrates Bayesian Experimental Design with large language models (LLMs) to better emulate real-world diagnostic reasoning.
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