Perspective Taking through Generating Responses to Conflict Situations

Although language model performance across diverse tasks continues to improve, these models still struggle to understand and explain the beliefs of other people. This skill requires perspective-taking, the process of conceptualizing the point of view of another person. Perspective taking becomes challenging when the text reflects more personal and potentially more controversial beliefs.We explore this task through natural language generation of responses to conflict situations. We evaluate novel modifications to recent architectures for conditioning generation on an individual’s comments and self-disclosure statements. Our work extends the Social-Chem-101 corpus, using 95k judgements written by 6k authors from English Reddit data, for each of whom we obtained 20-500 self-disclosure statements. Our evaluation methodology borrows ideas from both personalized generation and theory of mind literature. Our proposed perspective-taking models outperform recent work, especially the twin encoder model conditioned on self-disclosures with high similarity to the conflict situation.

  • Published in:
    Findings of the Association for Computational Linguistics Findings of the Association for Computational Linguistics
  • Type:
    Inproceedings
  • Authors:
    Plepi, Joan; Welch, Charles; Flek, Lucie
  • Year:
    2024

Citation information

Plepi, Joan; Welch, Charles; Flek, Lucie: Perspective Taking through Generating Responses to Conflict Situations, Findings of the Association for Computational Linguistics, Findings of the Association for Computational Linguistics, 2024, Plepi.etal.2024a,

Associated Lamarr Researchers

Prof. Dr. Lucie Flek

Prof. Dr. Lucie Flek

Area Chair NLP to the profile