arXiv 2609.37533 · cs.CL · 2026-09-29
E-MoE: Enhanced Mixture-of-Experts for Non-Factorized Diffusion Language Models
Arseny Ivanov, Alexander Kolesov, Alexander Korotin, Ivan Oseledets, Mikhail Goncharov
机构待核实
在最新榜 #255 本站收录于 2026-10-21
一句话要点
E-MoE 用增强的混合专家改进非分解式扩散语言模型，提升少步解码质量并避免后验坍塌。
E-MoE improves non-factorised diffusion language models with enhanced mixture-of-experts, raising few-step quality without posterior collapse.
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主题与学科
同主题：大语言模型
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- MemT-1.0: Towards Memory-Native Evolution ▲119
数据说明
元数据来自 arXiv API（已核实）；点赞来自 Hugging Face 每日论文；引用来自 Semantic Scholar。最近刷新 2026-10-22。
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