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EarlyEval: Cheaper Agent Evaluation via Early Outcome Prediction

110 upvotes · 2 SEP 2026 · Yuling Shi, Zhensu Sun, Junsen Dong et al.

This paper introduces EarlyEval, a method to reduce the cost of evaluating large language model (LLM) agents by predicting their outcomes early, allowing for earlier termination of agent runs. Practitioners may care because it can significantly reduce the computational cost of agent development.

continual learningagent evaluationreinforcement learningbenchmarkingefficiencycost-effectiveness