Search-Oriented Dialog System for Data Science

在R4中，对面向搜索的对话系统进行了全面的评估，发现了意图检测系统中的几个问题。我们对这些问题进行了研究，发现利用InstructGPT的少镜头学习可以有效地解决这些问题。在研究过程中，我们意识到最先进的预先培训的语言模型正在迅速发展，我们需要能够不断地利用这一点。我们对面向搜索的对话系统的体系结构进行了更改，以便我们可以轻松地整合外部语言资源，如预先训练的语言模型。有了新的架构，我们可以利用最近发布的预先训练的语言模型，包括chat GPT和GPT4，这大大提高了性能。

In R4, a thorough evaluation on the search-oriented dialog system was conducted, which revealed several problems in the intent detection system. We conducted research to solve the problems, and found that they could be effectively solved by utilizing few-shot learning with InstructGPT. During the research, we realized that the state-of-the-art of pre-trained language models were rapidly evolving, which we needed to be able to constantly leverage. We made a change to the architecture of the search-oriented dialog system, so that we can easily incorporate external language resources like pre-trained language models. With the new architecture, we could utilize recently released pre-trained language models, including chatGPT and GPT4, which led to much improved performance.