AI RESEARCH

Estimating the Empowerment of Language Model Agents

arXiv CS.AI

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