**When Agents Slow Down: Understanding LLM Agents' Test-Time Strategies via Elo-

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

> Large language model (LLM) agents allocate test-time compute adaptively as they revise solutions, use tools, explore alternatives, and decide when to stop. This test-time strategy makes it difficult to measure how agent performance scales. We study open-ended tasks that provide continuous scores for intermediate submissions, making progress observable throughout long trajectories. We propose Elo-per-token analysis, w...

**来源信息**
- **来源**：HuggingFace Daily Papers（社区热门论文）
- **分类**：ai-models
- **发布时间**：2026-09-15 08:00（北京时间）
- **原文**：[打开原文](https://huggingface.co/papers/2609.15309)