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Log-Depth Recurrent Language Modeling

Paper recorded by Signals 4 on 2026-09-23 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-23 on arXiv · recorded by Signals 4 on 2026-09-24

Category: cs.CL · 自然语言处理 · first seen 2026-09-24

Abstract

Language modeling using Transformers has become commonplace despite their fixed computational depth and quadratic runtime with respect to input tokens. Recurrent models on the other hand offer linear depth but no parallel execution. In this work, we extend balanced-tree recursive operators from sequence encoding to autoregressive prediction, enabling all prefix representations to be computed with

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#8 most recent of 239 cs.CL papers we have recorded · ↑ newer: Complementary Roles of Activation and Parametric Memory in Few-Shot Le · ↓ older: Exact Feedback Is Not Control: Evaluating Text-based Closed-Loop Revis
Cite this page: Log-Depth Recurrent Language Modeling: the #8 most recent of 239 cs.CL papers we have recorded (as of 2026-09-23). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/log-depth-recurrent-language-modeling.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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