Mathematical Reasoning in Large Language Models: Benchmarks, Architectures, Evaluation, and Open Challenges

In three linesSurvey of ~120 studies on mathematical reasoning in LLMs. Structured analysis of datasets, architectures, training strategies, and evaluation protocols. Identifies recurring failure modes: reasoning faithfulness, benchmark biases, generalization limitations.

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