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cs.AI2026
Representation Robustness Under Executable Reasoning Constraints in Large Language Models for Mathematical Problem Solving
Sagnik Nath, Edith Aurora Graf, Liang Zhang +1
Large language models (LLMs) are increasingly evaluated on mathematical problem solving, yet prior work often treats representationally equivalent formulations as interchangeable a…
cs.AI2026
A State-Transition Framework for Efficient LLM Reasoning
Liang Zhang, Yu Zhao, Longyue Wang +4
While Long Chain-of-Thought (CoT) reasoning significantly improves Large Language Models (LLMs) performance on complex reasoning tasks, the substantial computational and memory cos…
cs.AI2025
Mathematical Computation and Reasoning Errors by Large Language Models
Liang Zhang, Edith Aurora Graf
Large Language Models (LLMs) are increasingly utilized in AI-driven educational instruction and assessment, particularly within mathematics education. The capability of LLMs to gen…