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  <dc:date>2024-07-26</dc:date>
  <dc:title>查询式摘要数据集AMTQFSum及最优模型结果</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.16237</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>通过构建生成与自我校验提示链，基于ChatGPT和提示工程提出一种以大语言模型为&amp;ldquo;数据标注员&amp;rdquo;的自动化数据标注方法，构建了自然语言处理领域学术会议记录查询摘要数据集AMTQFSum。基于BART的查询式摘要生成效果最佳，ROUGE 1/2/L达52.53%、35.61%、44.80%。</dc:description>
  <dc:subject>查询式文本摘要; ChatGPT; 提示工程; 自动化数据标注; 学术会议记录</dc:subject>
  <dc:creator>jinling shang</dc:creator>
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  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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