交互式训练2：实时模型训练的可审计控制平面
Interactive Training 2: Auditable Control Plane for Live Model Training
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中文总结 AI 辅助
研究针对实时模型训练更改需特定代码的问题，提出交互式训练2这一开源控制平面，通过共享协议指导训练，经五个工作流程演示，其代码和跟踪为可审计训练提供了可重用基础。
中文摘要 AI 辅助
实验跟踪器展示训练进展，但更改实时运行通常仍需特定训练器代码。我们提出交互式训练2，这是一个通过共享协议指导训练的开源控制平面。训练应用声明其公开的设置和操作，人员和自动控制器通过同一接口提交请求，训练循环在安全控制点验证并应用这些请求。定制的Aim工作区将实时指标和控制与请求及结果的时间记录相结合。我们在五个自然语言处理和强化学习工作流程中演示了该系统。发布的代码和跟踪为可审计的人工和智能体引导训练提供了可重用基础。
英文摘要
Experiment trackers show how training is progressing, but changing a live run still usually requires trainer-specific code. We present Interactive Training 2, an open-source control plane for steering training through a shared protocol. Training applications declare which settings and actions they expose, humans and automated controllers submit requests through the same interface, and the training loop validates and applies them at safe control points. A customized Aim workspace combines live metrics and controls with a chronological record of requests and outcomes. We demonstrate the system across five NLP and reinforcement-learning workflows. The released code and traces provide a reusable foundation for auditable human- and agent-guided training.
发表机构
- University of Waterloo（滑铁卢大学）
- University of Wisconsin-Madison（威斯康星大学麦迪逊分校）
机构由 AI 辅助整理，请以论文原文为准。
