会话基础：基础行为与基础单元的标注与分析
Conversational Grounding: Annotation and Analysis of Grounding Acts and Grounding Units
AI总结：
针对对话系统基础行为能力不足的问题，采用基础行为、基础单元及基础程度标注两个对话语料库，构建基线模型测试大语言模型分类性能，为提升人机对话理解与可靠性提供资源支撑。
摘要：
成功的对话往往建立在共同理解的基础上，即所有各方对所共享的信息达成共识。这一过程被称为会话基础，对于构建能够准确跟踪和回忆共享信息的可信对话系统至关重要。智能体在为传达的信息进行基础处理方面的熟练程度，对构建可靠的对话系统具有重要意义。尽管对话系统近期取得了进展，但其基础能力仍存在明显不足。Traum提供了一个会话基础框架，引入了基础行为和基础单元，但尚未取得实质性进展，尤其是在大语言模型领域。为了弥补这一差距，我们使用基础行为、基础单元及其基础程度的度量，对两个对话语料库进行了标注。我们讨论了标注过程中的关键发现，并提供了一个基线模型，以测试当前语言模型在对话基础行为分类中的性能。我们的工作旨在为日常协作对话中使机器对话更易理解和更可靠的研究提供有用的资源。
英文摘要：
Successful conversations often rest on common understanding, where all parties are on the same page about the information being shared. This process, known as conversational grounding, is crucial for building trustworthy dialog systems that can accurately keep track of and recall the shared information. The proficiencies of an agent in grounding the conveyed information significantly contribute to building a reliable dialog system. Despite recent advancements in dialog systems, there exists a noticeable deficit in their grounding capabilities. Traum provided a framework for conversational grounding introducing Grounding Acts and Grounding Units, but substantial progress, especially in the realm of Large Language Models, remains lacking. To bridge this gap, we present the annotation of two dialog corpora employing Grounding Acts, Grounding Units, and a measure of their degree of grounding. We discuss our key findings during the annotation and also provide a baseline model to test the performance of current Language Models in categorizing the grounding acts of the dialogs. Our work aims to provide a useful resource for further research in making conversations with machines better understood and more reliable in natural day-to-day collaborative dialogs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
