arXiv Machine Learning June 16, 2026 By Jiarui Zhang, Yuchen Yang, Ran Yan, Zhiyu Mei, Liyuan Zhang, Daifeng Li, Wei Fu, Jiaxuan Gao, Shusheng Xu, Yi Wu, Binhang Yuan

AREAL-DTA: Dynamic Tree Attention for Efficient Reinforcement Learning of Large Language Models

Read the original on arXiv Machine Learning →

arXiv:2602. 00482v2 Announce Type: replace Abstract: Reinforcement learning (RL)-based post-training for large language models (LLMs) is computationally expensive, as it generates many rollout sequences that frequently share long token prefixes.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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