用语法语义信息提升语言模型生成质量，尤其对低资源语言有效
Infusing Prompts with Syntax and Semantics
- 将语法语义信息直接注入大模型，改进输出结构
- 在低资源语言翻译任务中超越现有最佳系统
- 适合关注生成质量与少样本场景的研究者
尽管取得显著成功，语言模型生成的文本常存在语法结构缺陷。我们分析了直接注入各类句法和语义信息对大型语言模型的影响。为验证方法价值，聚焦自然语言查询到SQL的翻译任务，特别关注比英语资源少的语言，以更深入探究低成本句法语义信息能带来多大帮助。结果表明，语言学分析可显著提升语言模型性能，使我们的系统超越此前最佳方案。
原文摘要 · Abstract (English)
Despite impressive success, language models often generate outputs with flawed linguistic structure. We analyze the effect of directly infusing various kinds of syntactic and semantic information into large language models. To demonstrate the value of our proposals, we focus on the translation of natural language queries to SQL, in particular dealing with languages with less resources than English, to better investigate how much help we can get from low cost syntactic and semantic information. We show that linguistic analysis can significantly boost language models, to the point that we have surpassed previous best systems.
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