LLMs show improved Bayesian inference with code execution

Researchers have developed a new evaluation framework to test the Bayesian inference capabilities of large language models (LLMs). The framework assesses LLMs' ability to update beliefs in context, a crucial aspect of scientific discovery. While current LLMs often violate Bayes' rule, the study found that models equipped with advanced reasoning and code execution abilities can significantly improve their performance, closely approximating complex posteriors. This suggests that LLMs with appropriate tools could soon accelerate AI-powered scientific discovery by enabling sophisticated belief updates. AI

IMPACT LLMs with code execution capabilities can approximate complex posteriors, potentially accelerating AI-powered scientific discovery.

RANK_REASON Research paper on LLM capabilities. [lever_c_demoted from research: ic=1 ai=1.0]

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