Papers › Open-Domain Dialog Evaluation using Follow-Ups Likelihood

Open-Domain Dialog Evaluation using Follow-Ups Likelihood

12 Sep 2022COLING 2022 10arXiv:2209.05185archive 2025-07-28

Maxime De Bruyn, Ehsan Lotfi, Jeska Buhmann, Walter Daelemans

Automatic evaluation of open-domain dialogs remains an unsolved problem. Moreover, existing methods do not correlate strongly with human annotations. This paper presents a new automated evaluation method using follow-ups: we measure the probability that a language model will continue the conversation with a fixed set of follow-ups (e.g., not really relevant here, what are you trying to say). When compared against twelve existing methods, our new evaluation achieves the highest correlation with human evaluations.

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Language ModelingLanguage ModellingOpen-Domain Dialog

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