CCL25-Eval任务7系统报告:学而不思则罔?

郑陈锐 郑陈锐; 朱奕澄 朱奕澄; 王欣雨 王欣雨; 姜伟麟 姜伟麟; 吴会腾 吴会腾

CCL25-Eval任务7系统报告:学而不思则罔?

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Abstract

"以DeepSeek-R1为代表 ,"思考"普遍被认为是一种提高大语言模型性能的方法。在CCL25-Eval"争鸣"中文阅读理解任务下,本文分别探索了"思考"和"非思考"两种模型在这项任务下的潜力。具体来说,在古代文学知识理解任务中,本文构建了古汉语特定领域的知识数据集,用大模型蒸馏了思考数据集,整理了高质量思考数据集,在这些数据基础之下同样lora微调,发现思考模型虽然性能有巨大提升,但依旧比不上原本的非思考模型。最后,开源并提交了基于Qwen2.5的SongPanda模型。"

Anthology ID:: 2025.ccl-2.32
Volume:: Proceedings of the 24th China National Conference on Computational Linguistics (CCL 2025)
Month:: August
Year:: 2025
Address:: Jinan, China
Editors:: Hongfei Lin, Bin Li, Hongye Tan
Venue:: CCL
SIG:
Publisher:: Chinese Information Processing Society of China
Note:
Pages:: 271–277
Language:
URL:: https://aclanthology.org/2025.ccl-2.32/
DOI:
Bibkey:
Cite (ACL):: 郑陈锐郑陈锐, 朱奕澄朱奕澄, 王欣雨王欣雨, 姜伟麟姜伟麟, and 吴会腾吴会腾. 2025. CCL25-Eval任务7系统报告:学而不思则罔?. In Proceedings of the 24th China National Conference on Computational Linguistics (CCL 2025), pages 271–277, Jinan, China. Chinese Information Processing Society of China.
Cite (Informal):: CCL25-Eval任务7系统报告:学而不思则罔? (郑陈锐 et al., CCL 2025)
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PDF:: https://aclanthology.org/2025.ccl-2.32.pdf

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@inproceedings{zheng-chen-rui-etal-2025-ccl25,
    title = "{CCL}25-Eval任务7系统报告:学而不思则罔?",
    author = "郑陈锐, 郑陈锐  and
      朱奕澄, 朱奕澄  and
      王欣雨, 王欣雨  and
      姜伟麟, 姜伟麟  and
      吴会腾, 吴会腾",
    editor = "Lin, Hongfei  and
      Li, Bin  and
      Tan, Hongye",
    booktitle = "Proceedings of the 24th {C}hina National Conference on Computational Linguistics ({CCL} 2025)",
    month = aug,
    year = "2025",
    address = "Jinan, China",
    publisher = "Chinese Information Processing Society of China",
    url = "https://aclanthology.org/2025.ccl-2.32/",
    pages = "271--277",
    abstract = "``以DeepSeek-R1为 代 表 ,{''}思 考{''}普 遍 被 认 为 是 一 种 提 高 大 语 言 模 型 性 能 的 方 法 。在CCL25-Eval{''}争鸣{''}中文阅读理解任务下,本文分别探索了{''}思考{''}和{''}非思考{''}两种模型在这项任务下的潜力。具体来说,在古代文学知识理解任务中,本文构建了古汉语特定领域的知识数据集,用大模型蒸馏了思考数据集,整理了高质量思考数据集,在这些数据基础之下同样lora微调,发现思考模型虽然性能有巨大提升,但依旧比不上原本的非思考模型。最后,开源并提交了基于Qwen2.5的SongPanda模型。''"
}

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    <abstract>“以DeepSeek-R1为 代 表 ,”思 考”普 遍 被 认 为 是 一 种 提 高 大 语 言 模 型 性 能 的 方 法 。在CCL25-Eval”争鸣”中文阅读理解任务下,本文分别探索了”思考”和”非思考”两种模型在这项任务下的潜力。具体来说,在古代文学知识理解任务中,本文构建了古汉语特定领域的知识数据集,用大模型蒸馏了思考数据集,整理了高质量思考数据集,在这些数据基础之下同样lora微调,发现思考模型虽然性能有巨大提升,但依旧比不上原本的非思考模型。最后,开源并提交了基于Qwen2.5的SongPanda模型。”</abstract>
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%0 Conference Proceedings
%T CCL25-Eval任务7系统报告:学而不思则罔?
%A 郑陈锐, 郑陈锐
%A 朱奕澄, 朱奕澄
%A 王欣雨, 王欣雨
%A 姜伟麟, 姜伟麟
%A 吴会腾, 吴会腾
%Y Lin, Hongfei
%Y Li, Bin
%Y Tan, Hongye
%S Proceedings of the 24th China National Conference on Computational Linguistics (CCL 2025)
%D 2025
%8 August
%I Chinese Information Processing Society of China
%C Jinan, China
%F zheng-chen-rui-etal-2025-ccl25
%X “以DeepSeek-R1为 代 表 ,”思 考”普 遍 被 认 为 是 一 种 提 高 大 语 言 模 型 性 能 的 方 法 。在CCL25-Eval”争鸣”中文阅读理解任务下,本文分别探索了”思考”和”非思考”两种模型在这项任务下的潜力。具体来说,在古代文学知识理解任务中,本文构建了古汉语特定领域的知识数据集,用大模型蒸馏了思考数据集,整理了高质量思考数据集,在这些数据基础之下同样lora微调,发现思考模型虽然性能有巨大提升,但依旧比不上原本的非思考模型。最后,开源并提交了基于Qwen2.5的SongPanda模型。”
%U https://aclanthology.org/2025.ccl-2.32/
%P 271-277

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Markdown (Informal)

[CCL25-Eval任务7系统报告:学而不思则罔?](https://aclanthology.org/2025.ccl-2.32/) (郑陈锐 et al., CCL 2025)

CCL25-Eval任务7系统报告:学而不思则罔? (郑陈锐 et al., CCL 2025)

ACL

郑陈锐郑陈锐, 朱奕澄朱奕澄, 王欣雨王欣雨, 姜伟麟姜伟麟, and 吴会腾吴会腾. 2025. CCL25-Eval任务7系统报告:学而不思则罔?. In Proceedings of the 24th China National Conference on Computational Linguistics (CCL 2025), pages 271–277, Jinan, China. Chinese Information Processing Society of China.