文件级错误定位新范式：用Agentic RAG让大模型智能追踪代码漏洞，准确率提升显著
arXiv:2605.17965v2 Announce Type: replace-cross Abstract: Bug localization remains a key bottleneck for large language model (LLM)-based software main…
从标准RAG到智能体RAG，提升伊斯兰教问答的忠实性与可靠性
arXiv:2601.07528v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly used for Islamic question answering, where ung…
经典RAG与Agentic RAG优劣对比，帮你避开“检索坑”做出明智选择
"Should I use RAG or an agent?" comes up in almost every LLM project I work on. The honest answer is that they are not competing choices. Classical RA…
提出CuSearch课程采样法，通过搜索深度优化Agentic RAG的强化学习训练，提升效率
arXiv:2605.11611v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a promising paradigm for trai…