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content/post/10/index.md

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- 论文作者:Sujin Chen, Kang Wang, Zixuan Zhou, Xiangyu Duan, Wanqun Zhang, Hao Yang, Jinsong Su, and Min Zhang
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- 完成单位:苏州大学,厦门大学
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- 论文简介:近年来,Text-to-SQL在自然语言接口与数据库交互中取得了显著进展,但现有研究大多集中于单轮问答场景,对于更贴近真实应用的多轮跨领域 Text-to-SQL任务缺乏系统性研究与评测。为此,本文提出并构建了一个专门面向多轮交互的跨领域 Text-to-SQL 评测资源,旨在填补当前研究中的空白。该资源在构建过程中充分考虑了用户与数据库交互的自然性与复杂性,设计了覆盖多领域的多轮问答数据,并引入语境依赖、语义消歧和跨表推理等真实挑战,以全面刻画多轮交互下的建模难点。基于该资源,研究者能够系统评估现有模型在多轮任务中的表现,从而揭示方法在领域迁移、上下文建模与鲁棒性方面的不足,为后续研究提供方向
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- 论文简介:当前机器翻译错误分析虽能定位错误,却​​缺乏对错误原因的系统化解译​​,导致基于LLM的自动分析方法存在解释可信度低、主观偏差大的缺陷。为此,本文提出​​双向锚定方案​​,通过构建首个手动标注的翻译错误解释评估资源,实现错误与原因的相互验证。本文首先设定前向锚定人工标注错误原因,后向锚定通过掩码解释反向定位错误,双向不一致时校准边界。同时,强制标注源语片段/修正片段等关键元素,设计错误专用模板,保障解释一致性。最后,本文基于4K条中英/英德实例验证LLM缺陷,进一步提出迭代双向锚定算法过滤误报,显著提升机器翻译错误检测能力

content/publication/163/index.md

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date: "2025-08-26T09:44:02Z"
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publishDate: "2025-08-26T09:44:02Z"
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publication_types: [directiona]
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publication: "**In Proc. of EMNLP 2025.** (CCF-B)"
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publication: "**In Proc. of EMNLP 2025** (CCF-B)"
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date: "2025-08-26T09:46:48Z"
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publishDate: "2025-08-26T09:46:48Z"
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publication_types: [direction5]
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publication: "**In Proc. of EMNLP 2025.** (CCF-B)"
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publication: "**In Proc. of EMNLP 2025** (CCF-B)"
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date: "2025-08-26T09:51:26Z"
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publishDate: "2025-08-26T09:51:26Z"
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publication: "**In Proc. of EMNLP 2025 findings.**"
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publication: "**In Proc. of EMNLP 2025 findings**"
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date: "2025-08-26T09:54:17Z"
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publication: "**In Proc. of EMNLP 2025 findings.**"
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date: "2025-08-26T09:59:07Z"
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publication: "**In Proc. of EMNLP 2025.** (CCF-B)"
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publication: "**In Proc. of EMNLP 2025** (CCF-B)."
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publication: "**In Proc. of EMNLP 2025 findings**"
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