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Main Authors: Alshomary, Milad, Lange, Felix, Booshehri, Meisam, Sengupta, Meghdut, Cimiano, Philipp, Wachsmuth, Henning
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2403.00662
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author Alshomary, Milad
Lange, Felix
Booshehri, Meisam
Sengupta, Meghdut
Cimiano, Philipp
Wachsmuth, Henning
author_facet Alshomary, Milad
Lange, Felix
Booshehri, Meisam
Sengupta, Meghdut
Cimiano, Philipp
Wachsmuth, Henning
contents Explanations are pervasive in our lives. Mostly, they occur in dialogical form where an {\em explainer} discusses a concept or phenomenon of interest with an {\em explainee}. Leaving the explainee with a clear understanding is not straightforward due to the knowledge gap between the two participants. Previous research looked at the interaction of explanation moves, dialogue acts, and topics in successful dialogues with expert explainers. However, daily-life explanations often fail, raising the question of what makes a dialogue successful. In this work, we study explanation dialogues in terms of the interactions between the explainer and explainee and how they correlate with the quality of explanations in terms of a successful understanding on the explainee's side. In particular, we first construct a corpus of 399 dialogues from the Reddit forum {\em Explain Like I am Five} and annotate it for interaction flows and explanation quality. We then analyze the interaction flows, comparing them to those appearing in expert dialogues. Finally, we encode the interaction flows using two language models that can handle long inputs, and we provide empirical evidence for the effectiveness boost gained through the encoding in predicting the success of explanation dialogues.
format Preprint
id arxiv_https___arxiv_org_abs_2403_00662
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Modeling the Quality of Dialogical Explanations
Alshomary, Milad
Lange, Felix
Booshehri, Meisam
Sengupta, Meghdut
Cimiano, Philipp
Wachsmuth, Henning
Computation and Language
Explanations are pervasive in our lives. Mostly, they occur in dialogical form where an {\em explainer} discusses a concept or phenomenon of interest with an {\em explainee}. Leaving the explainee with a clear understanding is not straightforward due to the knowledge gap between the two participants. Previous research looked at the interaction of explanation moves, dialogue acts, and topics in successful dialogues with expert explainers. However, daily-life explanations often fail, raising the question of what makes a dialogue successful. In this work, we study explanation dialogues in terms of the interactions between the explainer and explainee and how they correlate with the quality of explanations in terms of a successful understanding on the explainee's side. In particular, we first construct a corpus of 399 dialogues from the Reddit forum {\em Explain Like I am Five} and annotate it for interaction flows and explanation quality. We then analyze the interaction flows, comparing them to those appearing in expert dialogues. Finally, we encode the interaction flows using two language models that can handle long inputs, and we provide empirical evidence for the effectiveness boost gained through the encoding in predicting the success of explanation dialogues.
title Modeling the Quality of Dialogical Explanations
topic Computation and Language
url https://arxiv.org/abs/2403.00662