Unverified50% confidenceFactExact time
The study conducted a dual evaluation of 8 large language models, having them serve both as question setters generating misleading options and as answer solvers resolving the problems.
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50%
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Long-term
Relevance
9/11/2026
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UnverifiedThe study tested six mainstream large language models.74% similarUnverifiedLarge language models have a miscalibration problem, often answering in a confident tone regardless of whether the answer is correct or incorrect.74% similarUnverifiedLarge language models are trained on massive corpora that may already contain extensive mathematical literature, problem-solving processes, and even answers to similar problems.71% similarUnverifiedPost-processing and language model error correction are often the key to pushing from 90% to 99%, with methods including dictionary validation, regular expression rules, and language model error correction.71% similarUnverifiedSome large language models are capable of reproducing verbatim the questions and answers from popular benchmarks.70% similar
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