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English(EN) Nonobench: an open benchmark of 49 LLMs on nonogram puzzles, public and open source [P]

Nonobench基准测试在数图谜题上评估49个大型语言模型

一个名为Nonobench的新开源基准测试已发布,用于评估49个大型语言模型在数图谜题上的性能。该基准测试包括不同大小的标准谜题和旨在测试超越简单模式识别的逻辑的更具挑战性的随机谜题。结果显示,随着谜题复杂度的增加,解题率显著下降,GPT-6 Astra是唯一能够解决所有标准谜题的模型,而Claude Opus 5.5在更难的谜题上表现最佳。 AI

影响 为超越传统自然语言处理任务的大型语言模型推理能力提供了新的评估指标。

排序理由 该集群描述了一个用于评估大型语言模型在特定任务上表现的新开源基准测试。[lever_c_demoted from research: ic=1 ai=1.0]

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Nonobench基准测试在数图谜题上评估49个大型语言模型

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该集群描述了一个用于评估大型语言模型在特定任务上表现的新开源基准测试。[lever_c_demoted from research: ic=1 ai=1.0]
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Topics
paper, product
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High
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Breaking (< 6h)
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完整方法见我们的编辑标准。

报道来源 [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/mauricekleine ·

    Nonobench:一个包含49个大型语言模型在数独谜题上的公开开源基准测试 [P]

    <table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1wxa2bs/nonobench_an_open_benchmark_of_49_llms_on/"> <img alt="Nonobench: an open benchmark of 49 LLMs on nonogram puzzles, public and open source [P]" src="https://preview.redd.it/qfn8kr1ppeth1.png?width…