Dialogue participants often refer to entities or situations repeatedly within a conversation, which contributes to its cohesiveness. Subsequent references exploit the common ground accumulated by the interlocutors and hence have several interesting properties, namely, they tend to be shorter and reuse expressions that were effective in previous mentions. In this paper, we tackle the generation of first and subsequent references in visually grounded dialogue. We propose a generation model that produces referring utterances grounded in both the visual and the conversational context. To assess the referring effectiveness of its output, we also implement a reference resolution system. Our experiments and analyses show that the model produces better, more effective referring utterances than a model not grounded in the dialogue context, and generates subsequent references that exhibit linguistic patterns akin to humans.

本研究提出了一种基于视觉和对话环境的生成模型来产生有效指代话语，并实现了一个参照解析系统进行评估。实验结果表明，相比其它非对话背景下的模型，该模型能够产生更加有效的指代话语，而且在生成具有人类语言模式的后续指代方面表现出良好的效果。

在视觉和对话环境中生成后续参照：引用、重用、减少