Disagreement-Guided Weak-to-Strong Routing· 分歧引导的弱到强路由
Small language models are increasingly deployed on edge devices and robotic systems to meet cost and latency constraints, yet their limited capabilities can make reliable deployment challenging. Stronger models can provide assistance when needed, but deciding when to route a weak-model response to a stronger model often relies on signals of response correctness. In open-ended and agentic tasks, however, obtaining such signals can require costly ground-truth supervision that is difficult to obtain at scale. We revisit the foundations of weak-to-strong routing and ask whether routing decisions can instead be guided by signals that do not require ground-truth supervision. We first characterize the optimal weak-to-strong routing policy, while allowing for multiple weak-model responses generate
弱模型响应在无需真实监督的情况下，通过分歧信号路由到强模型。
- 核心方法
- 研究弱到强路由的基础，提出一种基于模型间分歧的路由策略，该策略不依赖于真实标签，能够根据多个弱模型的响应差异决定路由。
- 适合谁读
- 研究者 / 工程师
- 要解决的问题
- 如何在没有真实标签监督的情况下，决定何时将小型语言模型的响应路由到更强大的模型以提高可靠性。
- 关键实验
- 未提供
- 主要贡献
- 提供了一种无需真实标签监督的弱到强路由机制，优化了模型间的协作方式，降低了部署成本和延迟。
- 意义与局限
- 该方法在资源受限的边缘设备和机器人系统中具有重要应用价值，能够提高小型语言模型在开放性任务中的表现，但可能在特定领域任务中的准确性需要进一步验证。