将大语言模型与混合专家模型结合，攻克神经影像生存分析的可解释性难题，带来医学AI新思路。
arXiv:2607.08778v1 Announce Type: cross Abstract: Alzheimer's Disease (AD) is a complex neurodegenerative disorder that continues to impact millions o…
70多位作者联合发布Nemotron混合MoE大模型压缩方案，大幅降低推理成本且保持性能。
arXiv:2607.04371v1 Announce Type: new Abstract: We present Nemotron-Labs-3-Puzzle-75B-A9B, a compressed variant of Nemotron-3-Super optimized for inte…
多模型协作框架Fugu，协调GPT-5、Claude等专家模型，比单一巨模型更高效灵活
# Sakana Fugu: The Multi-Agent AI System That Works Like a Team We’ve all been there: copy-pasting a prompt from ChatGPT to Claude, and then to Gemini…
提出LongMoE模型，用轨迹感知混合专家机制应对多模态临床数据的任意模态缺失挑战。
arXiv:2606.09907v1 Announce Type: cross Abstract: Multimodal clinical learning is increasingly important for integrating diverse patient data, includi…
多模态MoE推理效率新突破：模态感知的容量扩展策略，实现计算资源动态分配。
arXiv:2605.05225v3 Announce Type: replace-cross Abstract: Mixture-of-Experts Multimodal Large Language Models (MoE MLLMs) suffer from a significant ef…
提出动态logit级门控机制，优化LLM专家路由效率，大幅降低推理成本。
arXiv:2606.04378v1 Announce Type: new Abstract: Leveraging multiple specialized LLMs can combine complementary strengths, but existing approaches trad…
用可微分最优传输优化MoE架构，提升大模型推理效率且训练更稳定。
arXiv:2606.01666v1 Announce Type: new Abstract: The scaling of Large Language Models (LLMs) has driven significant performance gains but created subst…
无需训练即可避免路由坍缩，专家特征向量为MoE提供高效非学习路由方案。
arXiv:2605.30992v1 Announce Type: new Abstract: Sparse Mixture of Experts (SMoE) architectures improve the training efficiency of Large Language Model…
英伟达推出5500亿参数Nemotron 3 Ultra开源模型，推理速度飙升5倍，还带来首个开源量子AI模型，硬核技术双响炮。
IT之家 6 月 1 日消息，为加强自主智能体的智能能力，英伟达今日发布了面向全天候运行智能体的全新开源模型与数据集，相关成果由英伟达 Nemotron 联盟联合打造。 据官方介绍，英伟达 Nemotron 3 Ultra 是一款拥有 5500 亿参数的混合专家模型，可为代码开发、科研及企业业务流程…
dMoE提出可学习块专家机制，为大型语言模型混合专家设计提供新思路，架构简洁高效。
arXiv:2605.30876v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to autoregres…
ICML 2026接收论文，提出异构多智能体范式，证明医疗AI中专家模型依然不可替代。
arXiv:2605.29744v1 Announce Type: new Abstract: The impressive performance of generalist large language models (LLMs) such as GPT and Claude in health…
提出Dense2MoE统一剪枝与升级方法，将稠密LLM转化为MoE架构，显著提升设备端大模型的效率与性能，推动帕累托前沿。
arXiv:2605.26496v1 Announce Type: cross Abstract: The Mixture of Experts MoE architecture is highly promising for resource constrained on device deplo…
首个将混合专家模型高效部署到移动设备上的架构，实现低延迟与资源友好的AI推理。
arXiv:2605.27358v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) has become the de facto architecture for hundred-billion-parameter language…
混合专家模型搬上太空网络，分布式推理的硬核尝试，论文新思路值得关注
arXiv:2605.00515v2 Announce Type: replace-cross Abstract: Leveraging continuous solar energy harvesting at high efficiency, space data centers are env…
最新研究：后训练MoE模型通过自蒸馏跳过一半专家，无需从头预训练，显著降低计算量。
arXiv:2605.18643v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) scales language models efficiently through sparse expert activation, and its …
用混合专家模型引导功能网络先验，脑解码准确性与可解释性双提升
arXiv:2605.19279v1 Announce Type: new Abstract: Visual image reconstruction from functional Magnetic Resonance Imaging (fMRI) is a fundamental task in…
22位作者联合研究，探索用大语言模型替代人类专家评估试题难度的方法与效果
arXiv:2605.18562v1 Announce Type: cross Abstract: Accurate estimates of item difficulty are essential for valid assessment and effective adaptive lear…
全新方法利用MoE正交生长，大幅节省LLM预训练成本，突破沉没成本陷阱。
arXiv:2510.08008v2 Announce Type: replace Abstract: As the computational demands for pre-training Large Language Models (LLMs) continue to surge, the …