TLDR Tech / AI
PACE: A Proxy for Agentic Capability Evaluation
PACE framework predicts costly agentic LLM benchmark performance using a small subset of atomic evaluation instances, achieving high accuracy at a fraction of the cost. It uses a regression model with selected instances from non-agentic benchmarks to predict scores on agentic benchmarks. PACE reduces evaluation costs by over 99% while maintaining a mean absolute error under 4%, aiding model development and selection.
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