从临床需求出发，系统梳理LLM在医疗推理中的进展与对齐挑战。
arXiv:2607.07761v1 Announce Type: new Abstract: Large language models (LLMs) have emerged as important tools in healthcare, showing growing potential …
综述LLM推理范式：快思考、慢思考与工具增强如何协同进化
arXiv:2508.12265v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable progress in reasoning across diverse dom…
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…
探索AI代理时代下多媒体与视觉分析的新范式，聚焦智能体如何重塑数据处理与交互方式。
arXiv:2504.06138v3 Announce Type: replace-cross Abstract: Professional users need tools to help them gain actionable insights from large multimedia co…
权威综述，系统梳理LLM集成学习在文本与代码生成中的方法、挑战与未来方向。
arXiv:2503.13505v3 Announce Type: replace-cross Abstract: Generative Pretrained Transformers (GPTs) are foundational Large Language Models (LLMs) for …
工业级大模型智能体系统综述，IEEE录用论文详解架构、应用与最新进展。
arXiv:2505.16120v3 Announce Type: replace Abstract: The emergence of Large Language Models (LLMs) has reshaped agent systems. Unlike traditional rule-…
系统梳理水下场景视觉增强与三维表示的近五年研究进展，涵盖成像退化、深度估计与重建方法，适合相关领域研究者快速把握学术脉络。
arXiv:2505.01869v2 Announce Type: replace Abstract: Underwater visual enhancement (UVE) and underwater 3D reconstruction pose significant challenges i…
全面综述LLM生成数据的质量与可信度评估方法，涵盖框架、指标与挑战，是相关研究者的必读参考。
arXiv:2601.17717v3 Announce Type: replace Abstract: Large Language Models (LLMs) have emerged as powerful tools for generating data across various mod…
用“周期表”系统梳理LLM推理的范式、方法与失败模式，结构清晰，综述全面，值得研究者细读。
arXiv:2606.11470v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved strong performance across natural language processing tasks…
arXiv上这篇综述系统梳理了建筑能源管理中的语义建模方法，52页丰富内容助你快速入门该领域。
arXiv:2404.11716v2 Announce Type: replace Abstract: Building Energy Management (BEM) is central to reducing energy use and CO2 emissions in the buildi…
联邦学习与大语言模型交叉领域的最新综述，由PAKDD 2026接收，系统梳理进展并展望未来方向。
arXiv:2409.15723v3 Announce Type: replace Abstract: Large Language Models have achieved impressive performance across diverse applications, yet their …
用流行病学系统综述检验AI科学知识合成的能力，揭示AI辅助文献分析的潜力与挑战
arXiv:2603.22327v2 Announce Type: replace-cross Abstract: Systematic literature reviews (SLRs) are a demanding and high-stakes form of scientific know…
系统梳理LLM Agent中证据追踪与执行溯源方法，为可信AI落地提供关键综述
arXiv:2606.04990v1 Announce Type: cross Abstract: Large language model (LLM)-based agents increasingly solve complex tasks by interacting with externa…
最新综述系统梳理神经3D网格纹理化技术进展，涵盖生成式方法、优化策略与评估基准，图形学研究者必读。
arXiv:2606.00137v1 Announce Type: new Abstract: Texturing 3D meshes plays a vital role in determining the visual realism of digital objects and scenes…
最新综述探讨LLM时代下图机器学习的前沿进展与融合方向
arXiv:2404.14928v3 Announce Type: replace-cross Abstract: Graphs play an important role in representing complex relationships in various domains like …
首篇系统性综述，梳理大规模AI基础模型在神经科学中的模型、数据集与应用，跨学科桥接的必读参考。
arXiv:2510.16658v3 Announce Type: replace Abstract: The development of large-scale artificial intelligence (AI) models is influencing neuroscience res…
免费GPU搭配AI Agent，让学术科研告别敲代码和通宵，论文复现、综述生成全自动搞定。
科研圈最大的谎言，就是只要Idea好，手里没卡也能发顶刊。 卡被大组垄断 实验室同门天天抢集群 自己卡在环境配置里动弹不得…… 没有资源、没有算力，这才是绝绝大多数科研狗的真实写照吧？ 看着同门天天有实验数据汇报，自己只能抱着几篇PDF干瞪眼。 他们给切问学术上线了一个逆天的【学术Agent】功能。
系统梳理LLM预训练数据暴露的成员推理、数据污染与安全影响，已被NLDB 2025接收，是研究数据隐私的必备综述。
arXiv:2605.26133v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become the predominant paradigm in NLP, advancing both research an…
从通信视角梳理LLM多智能体系统，揭示协作模式、协议设计与未来挑战，AI开发者必读综述。
arXiv:2502.14321v3 Announce Type: replace-cross Abstract: Large language model-based multi-agent systems have recently gained significant attention du…
首次系统综述具身AI安全，涵盖风险、攻击与防御，构建全面知识架构
arXiv:2605.02900v2 Announce Type: replace-cross Abstract: Embodied Artificial Intelligence (Embodied AI) integrates perception, cognition, planning, a…