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cs.AI2025
When Do Symbolic Solvers Enhance Reasoning in Large Language Models?
Zhiyuan He, Dingmin Wang
Large Reasoning Models (LRMs) achieve strong performance on complex reasoning tasks by generating long Chains of Thought (CoTs). However, this paradigm might incur substantial toke…
cs.AI2025
Exploring Depth Generalization in Large Language Models for Solving Recursive Logic Tasks
Zhiyuan He
Large language models have demonstrated remarkable capabilities across many tasks, yet face significant challenges when dealing with recursive reasoning problems, those requiring t…
cs.AI2025
Adapting Like Humans: A Metacognitive Agent with Test-time Reasoning
Yang Li, Zhiyuan He, Yuxuan Huang +5
Recent Vision-Language Models (VLMs) exhibit strong perceptual reasoning abilities, yet they often struggle to adapt efficiently when encountering novel tasks at test time. In cont…