DLLM解码计算并行化存在严重低效，只有少数token可解码，此文精准定位瓶颈并提出优化方向。
arXiv:2601.23278v2 Announce Type: replace Abstract: Diffusion Large Language Models (DLLMs) offer a compelling alternative to Auto-Regressive models, …
结合联合嵌入预测与掩码扩散，提出全新语言模型预训练架构
arXiv:2606.00091v1 Announce Type: cross Abstract: Joint Embedding Predictive Architectures (JEPAs) have reshaped self-supervised representation learni…
联邦学习与大模型安全结合的新方案，通过宪法AI与安全过滤提升可信度
arXiv:2502.16691v2 Announce Type: replace Abstract: Recent research has increasingly focused on training large language models (LLMs) using federated …
新型扩散语言模型并行解码方法DMax，通过自精炼机制减少误差累积，实现高并行度高质量生成。
arXiv:2604.08302v3 Announce Type: replace-cross Abstract: We present DMax, a new paradigm for efficient diffusion language models (dLLMs). It mitigate…