扩散模型先验知识赋能人物搜索新范式，精准提升行人重识别效果
arXiv:2510.01841v2 Announce Type: replace Abstract: Person search aims to jointly perform person detection and re-identification by localizing and ide…
让大模型在稀疏奖励环境中引导强化学习策略，通过不确定性估计提升决策可靠性，有代码可复现。
arXiv:2606.06673v1 Announce Type: new Abstract: Sparse rewards and heterogeneous task sequences remain persistent challenges in Reinforcement Learning…
ICML 2026论文揭示：LLM代码理解靠先验知识，而非编程语言语义
arXiv:2510.03415v3 Announce Type: replace-cross Abstract: Recent work asks whether large language models (LLMs) condition their reasoning on explicit …
将次线性图算法的先验知识理论引入LLM测试时优化，开辟AI效率提升新路径。
arXiv:2510.16609v3 Announce Type: replace Abstract: Test-time augmentation, such as Retrieval-Augmented Generation (RAG) or tool use, critically depen…
最新研究系统对比LLM智能体在硬件感知代码优化中依赖先验知识还是搜索策略，揭示两者优劣边界
arXiv:2605.19782v1 Announce Type: cross Abstract: LLM discovery and optimization systems are increasingly applied across domains, implementing a commo…
Flow Matching结合优化子类先验，为医学图像增强提供新方案。
arXiv:2605.16469v1 Announce Type: cross Abstract: Rare diseases dominate the diagnostic challenge in medical imaging yet are severely underrepresented…