PMIScore: An Unsupervised Approach to Quantify Dialogue Engagement
High dialogue engagement is a crucial indicator of an effective conversation. A reliable measure of engagement could help benchmark large language models, enhance the effectiveness of human-computer interactions, or improve personal communication skills. However, quantifying engagement is challenging, since it is subjective and lacks a "gold standard". This paper proposes PMIScore, an efficient unsupervised approach to quantify dialogue engagement. It uses pointwise mutual information (PMI), which is the probability of generating a response conditioning on the conversation history. Thus, PMIScore offers a clear interpretation of engagement. As directly computing PMI is intractable due to ...
| Authors | Yongkang Guo, Zhihuan Huang, Yuqing Kong |
|---|---|
| Primary category | cs.CL |
| Published | 14 March 2026 |
| Last updated at source | 14 March 2026 |
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