Any Other Thoughts, Hedgehog? Linking Deliberation Chains in Collaborative Dialogues
This work addresses the challenge of understanding knowledge construction in collaborative dialogues, which is incremental as it builds on existing methods for dialogue analysis.
The paper tackled the problem of modeling causal relations that lead to probing questions in collaborative dialogues by introducing a graph-based framework of deliberation chains, reframing it as a coreference-style clustering problem, and demonstrated effectiveness on datasets like the Weights Task and DeliData, establishing a performance standard.
Question-asking in collaborative dialogue has long been established as key to knowledge construction, both in internal and collaborative problem solving. In this work, we examine probing questions in collaborative dialogues: questions that explicitly elicit responses from the speaker's interlocutors. Specifically, we focus on modeling the causal relations that lead directly from utterances earlier in the dialogue to the emergence of the probing question. We model these relations using a novel graph-based framework of deliberation chains, and reframe the problem of constructing such chains as a coreference-style clustering problem. Our framework jointly models probing and causal utterances and the links between them, and we evaluate on two challenging collaborative task datasets: the Weights Task and DeliData. Our results demonstrate the effectiveness of our theoretically-grounded approach compared to both baselines and stronger coreference approaches, and establish a standard of performance in this novel task.