首页> 外文会议>Workshop on Document-grounded Dialogue and Conversational Question Answering >DialDoc 2021 Shared Task: Goal-Oriented Document-grounded Dialogue Modeling
【24h】

DialDoc 2021 Shared Task: Goal-Oriented Document-grounded Dialogue Modeling

机译:DeloDoc 2021共享任务:面向目标的文档接地对话建模

获取原文

摘要

We present the results of Shared Task at Workshop DialDoc 2021 that is focused on document-grounded dialogue and conversational question answering. The primary goal of this Shared Task is to build goal-oriented information-seeking conversation systems that can identify the most relevant knowledge in the associated document for generating agent responses in natural language. It includes two subtasks on predicting agent responses: the first subtask is to predict the grounding text span in the given document for next agent response: the second subtask is to generate agent response in natural language given the context. Many submissions outperform baseline significantly. For the first task, the best-performing system achieved 67.1 Exact Match and 76.3 F1. For the second subtask, the best system achieved 41.1 SacreBLEU and highest rank by human evaluation.
机译:我们提出了共享任务的结果在车间DALDOC 2021,专注于文档接地对话和对话问答。这个共享任务的主要目标是构建面向目标的信息搜索对话系统,该系统可以识别相关文档中最相关的知识,以生成自然语言中的代理响应。它包括两个子任务:第一个子任务是为下一个agent响应预测给定文档中的基本文本跨度;第二个子任务是在给定上下文的情况下,以自然语言生成agent响应。许多意见书的表现明显优于基准。在第一个任务中,表现最好的系统实现了67.1次精确匹配和76.3次F1。对于第二个子任务,最佳系统达到了41.1 SacreBLEU,并且通过人类评估排名最高。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号