AI RESEARCH
Estimating the Empowerment of Language Model Agents
arXiv CS.AI
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ArXi:2509.22504v3 Announce Type: replace As language model (LM) agents become increasingly capable and adopted in real-world applications, there is a growing need for scalable evaluation frameworks beyond costly, manually designed benchmarks. We propose information-theoretic evaluation based on empowerment, an information-theoretic measure of an agent's influence on future states through its actions. To handle the unique challenges of text-based environments, we