20 citations · 22 across the 8 of their papers we have counts for
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cs.AI2026
HyperGuide: Hyperbolic Guidance for Efficient Multi-Step Reasoning in Large Language Models
Yuyu Liu, Haotian Xu, Yanan He +3
Searching over alternative continuations lets large language models (LLMs) compare the downstream consequences of a reasoning step before committing to it, but expanding and evalua…
cs.AI2025
Agent RL Scaling Law: Agent RL with Spontaneous Code Execution for Mathematical Problem Solving
Xinji Mai, Haotian Xu, Zhong-Zhi Li +5
Large Language Models (LLMs) often struggle with mathematical reasoning tasks requiring precise, verifiable computation. While Reinforcement Learning (RL) from outcome-based reward…
cs.AI2025★ 20 cited
From System 1 to System 2: A Survey of Reasoning Large Language Models
Zhong-Zhi Li, Duzhen Zhang, Ming-Liang Zhang +18
Achieving human-level intelligence requires refining the transition from the fast, intuitive System 1 to the slower, more deliberate System 2 reasoning. While System 1 excels in qu…