提出Caption Bottleneck模型，通过瓶颈模块压缩视觉特征并生成描述，在ECCV 2026上展现多模态理解新范式。
arXiv:2607.00578v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) provide interpretability by routing predictions through a layer of hu…
探究数据混合与模型架构对非洲语言持续预训练的影响，为低资源语言建模提供前沿实证与设计指南。
arXiv:2601.06395v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly multilingual, yet open models continue to underperfo…
KDD 2026论文提出Tokenized MoE框架，用专家混合机制突破GNN泛化瓶颈
arXiv:2602.09258v2 Announce Type: replace Abstract: Deployed graph neural networks (GNNs) are frozen at deployment yet must fit clean data, generalize…
网友质疑Anthropic新模型Claude Fable 5是全新架构还是仅数据优化，引发版本命名逻辑讨论
I am trying to understand why Claude Fable 5 is different, is it a new architecture, or trained from scratch or just a better fine tuning on top of Op…
Claude与ChatGPT的"思考投入"机制是独立模型还是同参数不同效果？作者通过缓存行为差异切入，探讨大模型推理能力的实现方式。
Claude and ChatGPT have thinking efforts where you can tune the amount of thinking allowed. Like low, medium, high, xhigh and so on. But are they diff…
提出语义层级感知的层次记忆Transformer，突破长文本建模瓶颈，架构设计颇具新意。
arXiv:2605.24930v1 Announce Type: new Abstract: Transformer-based LLMs achieve strong results on many language tasks; however, long inputs remain chal…
中国工业物理AI为何领先？江行智能用99%准确率的算法和三层模型，在新能源与电网领域实现规模化落地。
中国工业物理AI的真正优势不在模型参数，而在全球12倍的工业机器人部署密度、两倍的发电量和密集的5G边缘节点——场景密度、基建底座和开源模型的合力，正在推动物理AI从实验室走向规模化落地。 江行智能提出工业物理AI的三层模型，这套系统已在新能源场站和电网巡检场景落地——覆盖贵州、内蒙古等多地，核心算…