arXiv 2610.07591 · cs.CL · 2026-10-06
Recurrent Looped Transformer
Yifan Zhang, Jichen Feng, Shihan Qin, Sun-Yuan Kung, Mengdi Wang
Princeton University
在最新榜 #118 本站收录于 2026-10-21
一句话要点
循环 Transformer 新结构 RLT 让计算深度随序列增长，奇偶校验等任务可泛化到远超训练长度。
The Recurrent Looped Transformer lets compute depth grow with sequence length, generalising tasks like parity far beyond training length.
阅读 arXiv 原文 PDF Hugging Face 讨论 代码仓库 项目页
主题与学科
同主题：大语言模型
- Jeva: System One Models from First Principles ▲371
- Post-Training Leaves Behavioral Shadows on Unrelated Decisions ▲273
- OmniEdu: Open Foundation Models for Learning and Teaching ▲240
- PAR: Progress-Aligned Recurrence for Length Generalization in State Tracking ▲148
- 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。
要点由本站根据摘要自写，不转载摘要原文，请阅读原文。