新闻
Learning When to Think: Adaptive Reasoning for Test-Time Compute Allocation
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers trained a reasoning model to choose between three response modes: quick answer, brief reasoning, or extended reasoning, reducing token use by 41 percent.
- 为何重要
- Engineers building inference systems care about this when balancing accuracy against computational cost and latency in production deployments.
- 注意
- Results shown on math problems; transfer to other domains and scaling to larger models remain unvalidated questions.
收听本摘要
- language model
- reasoning
- token
- reinforcement learning
- grpo
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