mlsanityData to 14 Oct 2026

EMP-EVAL: A Framework for Measuring Empathy in Open Domain Dialogues

arXiv 2301.12510 ↗First posted 29 Jan 2023cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

Measuring empathy in conversation can be challenging, as empathy is a complex and multifaceted psychological construct that involves both cognitive and emotional components. Human evaluations can be subjective, leading to inconsistent results. Therefore, there is a need for an automatic method for measuring empathy that reduces the need for human evaluations. In this paper, we proposed a novel approach EMP-EVAL, a simple yet effective automatic empathy evaluation method. The proposed technique takes the influence of Emotion, Cognitive and Emotional empathy. To the best knowledge, our work is the first to systematically measure empathy without the human-annotated provided scores. Experimental results demonstrate that our metrics can correlate with human preference, achieving comparable results with human judgments.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 22 references that are in the map. First posted on arXiv 29 Jan 2023.

Builds on

9 of 22 references.

References · 9

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  3. 2019DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generationcited by 842
  4. 2017DailyDialog: A Manually Labelled Multi-turn Dialogue Datasetcited by 652
  5. 2020A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Supportcited by 182
  6. 2019Facebook FAIR's WMT19 News Translation Task Submissioncited by 179
  7. 2018Modeling Empathy and Distress in Reaction to News Storiescited by 52
  8. 2019Learning Word Ratings for Empathy and Distress from Document-Level User Responsescited by 10
  9. 2019Attention-based Modeling for Emotion Detection and Classification in Textual Conversationscited by 5

Built on by

Not cited yet.