评分 6.3 · 来源：cs.AI updates on arXiv.org · 发布于 2026-04-08
评分依据：自主深度学习实验Agent框架
arXiv:2604.05854v1 Announce Type: new Abstract: We present \textbf{Deep Researcher Agent}, an open-source framework that enables large language model (LLM) agents to autonomously conduct deep learning experiments around the clock. Unlike existing AI research assistants that focus on paper writing or code generation, our system addresses the full experiment lifecycle: hypothesis formation, code implementation, training execution, result analysis, and iterative refinement. The framework introduces three key innovations: (1) \textbf{Zero-Cost Monitoring} — a monitoring paradigm that incurs zero