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SchmidhuberAI releases a new paper proposing a curiosity-driven planning method for LLM testing and generation
ME News Update, April 16 (UTC+8), a new paper titled “Planning to Explore: Curiosity-Driven Planning for LLM Test Generation” has been published. The study formalizes the test generation for large language models (LLMs) as a Bayesian exploration problem. The paper points out that, in terms of branch coverage metrics, planning-aware methods significantly outperform greedy approaches. (Source: InFoQ)