一种循环状态空间模型，通过深度递归和输入重塑提升时间序列分类性能，参数更少效果更优。
arXiv:2605.16048v1 Announce Type: cross Abstract: State Space Models (SSMs) are inherently recurrent along the sequence dimension, yet depth-recurrenc…
首个能编辑递归语言模型缓存写入的稀疏自编码器，突破残差SAE局限。
arXiv:2605.12770v2 Announce Type: replace-cross Abstract: We introduce WriteSAE, the first sparse autoencoder that decomposes and edits the matrix cac…
突破二次复杂度瓶颈，高阶线性注意力HLA以线性时间实现更强交互，为长上下文模型提供新方向。
arXiv:2510.27258v3 Announce Type: replace-cross Abstract: The quadratic cost of scaled dot-product attention is a central obstacle to scaling autoregr…
对Mamba等状态空间模型提出隐藏状态中毒攻击，揭示其对抗鲁棒性重大漏洞，引发对新型LLM安全性的反思。
arXiv:2601.01972v4 Announce Type: cross Abstract: State space models (SSMs) like Mamba offer efficient alternatives to Transformer-based language mode…