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Yi Hu

ACL 2026×2ICML 2026推理可解释性长上下文与架构强化学习与后训练理论与学习动力学
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合作网络12
1 一作 · 3 篇 · ACL 2026 / ICML 2026

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2026 顶会论文

3
一作ACL 2026Poster· Natural Language Processing

Towards a Mechanistic Understanding of Large Reasoning Models: A Survey of Training, Inference, and Failures

Yi Hu · Jiaqi Gu · Ruxin Wang · Zijun Yao · Hao Peng · Xiaobao Wu · Jianhui Chen · Muhan Zhang · Liangming Pan

摘要

Reinforcement learning (RL) has catalyzed the emergence of Large Reasoning Models (LRMs) that have pushed reasoning capabilities to new heights. While their performance has garnered significant excitement, exploring the internal mechanisms driving these behaviors has become an equally critical re...

可解释性强化学习与后训练理论与学习动力学OpenReview 项目页
作者位次 #2/3ACL 2026Poster· Natural Language Processing

S ub T oken T est: A Practical Benchmark for Real-World Sub-token Understanding

Shuyang Hou · Yi Hu · Muhan Zhang

摘要

Recent advancements in large language models (LLMs) have significantly enhanced their reasoning capabilities. However, they continue to struggle with basic character-level tasks, such as counting letters in words—a problem rooted in their tokenization process. While existing benchmarks have highl...

推理评测与基准可解释性OpenReview 项目页

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