Unverified50% confidenceBenchmarkExact time
Some large language models have already achieved over 80% accuracy on competition-level problem sets such as MATH and AIME.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
9/12/2026
First Seen
Valid until: 12/11/2026
Sources
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Unverified使用领域专业术语的Prompt相比自然语言描述，能使大语言模型的代码生成准确率提升40%以上73% similarUnverifiedEnglish content typically accounts for 60%–80% of the training data in mainstream large language models.72% similarUnverifiedStructured prompts can improve the output quality of large language models by 40%–60% compared to vague descriptions.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.70% similar
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