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When Agents Slow Down: Understanding LLM Agents' Test-Time Strategies via Elo-per-token Analysis

The paper explores how LLM agents use test-time compute to improve solutions, introducing Elo-per-token analysis to measure performance scaling. It finds that agents initially outperform independent sampling but eventually lag behind, while humans show sustained improvement.

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PublishedSeptember 14, 2026Kaiyuan Liu, Qiuyang Mang, Bo Peng
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WHY IT MAY MATTER

This research provides insights into how LLM agents utilize computational resources during testing, helping to optimize their performance and understand their limitations.

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