新闻
On Turn-Level Best-of-N Sampling for Scaling LLM Agents
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers tested turn-level best-of-N sampling for LLM agents, where one model generates candidate actions and another selects the best one at each step.
- 为何重要
- Matters for engineers building long-horizon autonomous agents who want inference-time improvements without retraining models.
- 注意
- Results show 5-10% accuracy gains on tested tasks, but generalization to other domains and the computational cost of running multiple models remains unclear.
- agent
- llm
- language model
- inference
- eval
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