ResearchResearch paperLarge Language Models · Interpretability · Multimodal Models1 source · Oct 9, 2026

What We Talk About When We Talk About Emotion Editing

Emotional image editing aims to change the emotion a scene conveys while preserving its essential content.

Key points

  • Because the same scene can support different emotional interpretations, achieving an emotional goal requires visual changes grounded in the source context.
  • Motivated by the Component Process Model, which links emotional responses to event appraisal, we investigate neural representations as a reference for these editing decisions.
  • Using TRIBE v2, an fMRI encoding model, we analyze 400 source-target pairs across eight emotion categories.
  • Hidden states from EmoEdit, EmoEditor, and AffectDelta correspond more strongly to predicted target-image responses in visual regions than in affect-related regions.

Sources (1)

  • [1]What We Talk About When We Talk About Emotion Editing
    arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 9, 01:13 PM
    Emotional image editing aims to change the emotion a scene conveys while preserving its essential content.
    Because the same scene can support different emotional interpretations, achieving an emotional goal requires visual changes grounded in the source context.

Extractive summary: sentences quoted from the sources.

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