Abstract
Active participation in a conversation is key to building common ground, since understanding is jointly tailored by producers and recipients. Overhearers are deprived of the privilege of performing grounding acts and can only conjecture about intended meanings. Still, data generation and annotation, modelling, training and evaluation of NLP dialogue models place reliance on the overhearing paradigm. How much of the underlying grounding processes are thereby forfeited? As we show, there is evidence pointing to the impossibility of properly modelling human meta-communicative acts with data-driven learning models. In this paper, we discuss this issue and provide a preliminary analysis on the variability of human decisions for requesting clarification. Most importantly, we wish to bring this topic back to the community's table, encouraging discussion on the consequences of having models designed to only "listen in".
Abstract (translated)
对话中的积极参与是建立共同基础的关键，因为理解是由生产者和接收者共同调整的。听者被剥夺了执行补足行为的特权，只能猜测意图。尽管如此，数据生成、注释、建模、训练和评估自然语言对话模型的过程仍然依赖于听者范式。因此，有多少 underlying 补足过程被放弃了呢？正如我们所看到的，有证据表明，用数据驱动的学习模型正确建模人类元交际行为是不可能的。在本文中，我们讨论了这个问题，并对人类请求澄清的决策的变异性进行了初步分析。最重要的是，我们希望将这个话题带回社区的讨论中，鼓励大家讨论设计仅能“听”的模型的后果。
URL
https://arxiv.org/abs/2405.01139
