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…
从几何先验到照片级逼真，这篇Eurographics 2026 STAR综述系统梳理了构建数字人的全链路核心技术。
arXiv:2607.04341v1 Announce Type: cross Abstract: This state-of-the-art report provides an overview of controllable 3D human avatar creation. We descr…
大模型先验如何提升程序搜索中的经验风险最小化？理论+方法前沿新作
arXiv:2510.14331v3 Announce Type: replace Abstract: We study program-learning methods that are efficient in both samples and computation. Classical le…
医学MRI重建新突破：高维嵌入先验巧解噪声K空间恢复难题，扩散模型再显神通
arXiv:2607.01176v1 Announce Type: new Abstract: Magnetic resonance imaging (MRI) reconstruction under realistic acquisition conditions can be fundamen…
量化RAG系统的先验主导，破解认知盲点，提升知识检索与生成的可信度。
arXiv:2606.23695v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds Large Language Models in external knowledge, yet curren…
用结构先验强化大模型处理表格数据预测，一项提升LLM表格推理能力的创新方法。
arXiv:2510.17385v5 Announce Type: replace-cross Abstract: Tabular prediction has long been dominated by gradient-boosted decision trees and specialize…
将热核先验引入流形变分框架，为贝叶斯深度学提供新的几何先验设计思路。
arXiv:2606.18658v1 Announce Type: new Abstract: Learning unsupervised representations of medical imaging cohorts can reveal clinically meaningful prot…
多模态先验注入表示空间去噪，RepFusion实现更鲁棒的跨模态表征融合。
arXiv:2606.14700v1 Announce Type: new Abstract: Large language models (LLMs) are widely used in text-to-image (T2I) systems, but they are typically li…
揭秘大模型在结构化数据上的“卡壳”瞬间：类别先验锁定如何让上下文学习失效
arXiv:2606.11961v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as conditional generators for structured data, re…
新基准ChronoPhyBench直击核心：多模态大模型靠语言先验伪装理解？物理时序推理能力堪忧！
arXiv:2606.07962v1 Announce Type: new Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficien…
先验引导的想象采样机制，解决世界模型在连续控制规划中候选动作生成的关键难题。
arXiv:2606.07974v1 Announce Type: cross Abstract: A learned world model provides a powerful physical intuition for evaluating future states. But its e…
多视角捕捉面部毛发从稀疏到浓密，无需先验知识即可实现毛流级精细重建
arXiv:2606.08041v1 Announce Type: cross Abstract: Facial hair is a defining trait of personal identity, yet remains a critical bottleneck for digital …
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…
利用患者历史MRI数据实现个性化快速扫描，显著提升图像重建质量与速度
arXiv:2606.04419v1 Announce Type: cross Abstract: MRI provides excellent soft-tissue contrast without ionizing radiation, but long acquisition times i…
用流行病学模型探针LLM行为先验，跨学科方法揭示大模型内在规律。
arXiv:2606.02867v1 Announce Type: cross Abstract: Human behaviour during epidemics affects infectious disease dynamics, but quantifying this remains d…
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 …
结合GPS轨迹与大语言模型，创新提出季节性先验与活动链生成方法，提升旅游移动性建模精度。
arXiv:2605.29578v1 Announce Type: new Abstract: Tourist mobility poses a distinct challenge for urban transportation planning. Unlike resident commuti…
提出先验校正正交信任区域引导，优化动作分块流策略，平滑性与性能兼得。
arXiv:2605.24433v1 Announce Type: cross Abstract: Flow-matching robot policies commonly use action-chunking inference for efficient closed-loop contro…
用场景重建生成地图先验，大幅提升3D目标检测精度，CVPR 2026前沿论文。
arXiv:2605.22997v1 Announce Type: new Abstract: In autonomous driving, mapping is critical for motion planning but remains an under-utilized resource …
利用大模型蕴含的稀疏性先验，为高维数据特征选择提供鲁棒策略，理论贡献显著。
arXiv:2605.23102v1 Announce Type: cross Abstract: Large language models (LLMs) offer a scalable mechanism to elicit domain-informed prior information …