硬件反馈驱动的迭代优化新范式，Embedded Arena为嵌入式系统场景提供高效搜索策略
arXiv:2606.16190v1 Announce Type: cross Abstract: Embedded devices from wildlife monitoring stations to clinical wearables require local AI inference …
用大语言模型自主设计量子电路，打破人类依赖，7组件框架实现迭代优化。
arXiv:2606.13380v1 Announce Type: cross Abstract: The design of high performing quantum circuits remains largely dependent on human expertise. We intr…
通用提示改进可能适得其反，这篇论文用严谨的评估驱动迭代方法，给出LLM应用避坑指南。
arXiv:2601.22025v2 Announce Type: replace-cross Abstract: Evaluating Large Language Model (LLM) applications differs from conventional software testin…
文学翻译高质量数据稀缺？新框架用多维度迭代生成参考与偏好数据，提升LLM翻译流畅性与文学效果。
arXiv:2606.05924v1 Announce Type: cross Abstract: Literary translation poses unique challenges due to the scarcity of high-quality annotated data and …
揭示LLM迭代优化中的脆弱性：仅9%的智能体能成功自改进，挑战何在？
arXiv:2603.23994v2 Announce Type: replace-cross Abstract: Generative optimization uses large language models (LLMs) to iteratively improve artifacts (…
提出针对LLM代理的间接提示注入攻击新方法，利用反馈引导迭代优化提升攻击效果，值得AI安全研究者关注。
arXiv:2605.24659v1 Announce Type: new Abstract: LLM-based agents are increasingly deployed for complex tasks requiring planning, tool use, and interac…
用迭代奖励引导后训练，让表格语言模型也能自我进化、持续提升性能。
arXiv:2604.18966v2 Announce Type: replace Abstract: Tabular language models can generate synthetic tables by modeling rows as token sequences, but the…
多智能体LLM工作流的离线评估与迭代优化新框架，即将亮相ACL 2026，助力复杂协作场景调优。
arXiv:2605.18032v1 Announce Type: new Abstract: Multi-agent LLM workflows -- systems composed of multiple role-specific LLM calls -- often outperform …