1. Paper title
Recursive Template-based Frame Generation for Task Oriented Dialog
2. link
https://www.aclweb.org/anthology/2020.acl-main.186.pdf
3. 摘要
The Natural Language Understanding (NLU) component in task oriented dialog systems processes a user’s request and converts it into structured information that can be consumed by downstream components such as the Dialog State Tracker (DST). This information is typically represented as a semantic frame that captures the intent and slot-labels provided by the user. We first show that such a shallow representation is insufficient for complex dialog scenarios, because it does not capture the recursive nature inherent in many domains. We propose a recursive, hierarchical frame-based representation and show how to learn it from data. We formulate the frame generation task as a template-based tree decoding task, where the decoder recursively generates a template and then fills slot values into the template. We extend local tree-based loss functions with terms that provide global supervision and show how to optimize them end-to-end. We achieve a small improvement on the widely used ATIS dataset and a much larger improvement on a more complex dataset we describe here.
4. 要解决什么问题
Natural Language Understanding (NLU) component基于用于输入生成的信息的表示不足以应对复杂的对话场景。
5. 作者的主要贡献
基于输入信息生成一个recursive, hierarchical frame-based表示
[?] 没看懂
同时使用recursive的方法解码
6. 得到了什么结果
在ATIS数据集上有较小的进步。
在更复杂的数据集上有较大的进步。