# Anatomy of a Feeling: Narrating Embodied Emotions via Large Vision-Language Models

arXiv: https://arxiv.org/abs/2509.19595 · HTML: https://mlsanity.com/paper/2509.19595/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Placed in Multimodal emotion understanding, one of 16 directions in Multimodal LLMs / vision-language models.
- Builds on 15 of its 39 references that are in the map.
- First posted on arXiv 23 Sep 2025.

## Placed in

- Multimodal LLMs / vision-language models / [Multimodal emotion understanding](https://mlsanity.com/mllm/multimodal-emotion-understanding/)

## Builds on (most cited first, 15 of 15)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [The Llama 3 Herd of Models](https://mlsanity.com/paper/2407.21783/) (2024)
- [Improved Baselines with Visual Instruction Tuning](https://mlsanity.com/paper/2310.03744/) (2023)
- [Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution](https://mlsanity.com/paper/2409.12191/) (2024)
- [Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling](https://mlsanity.com/paper/2501.17811/) (2025)
- [Context Based Emotion Recognition using EMOTIC Dataset](https://mlsanity.com/paper/2003.13401/) (2020)
- [End-to-End Multimodal Emotion Recognition using Deep Neural Networks](https://mlsanity.com/paper/1704.08619/) (2017)
- [EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis](https://mlsanity.com/paper/2401.08508/) (2024)
- [Survey on Emotional Body Gesture Recognition](https://mlsanity.com/paper/1801.07481/) (2018)
- [Evaluating Vision-Language Models for Emotion Recognition](https://mlsanity.com/paper/2502.05660/) (2025)
- [VLLMs Provide Better Context for Emotion Understanding Through Common Sense Reasoning](https://mlsanity.com/paper/2404.07078/) (2024)
- [A Survey on Facial Expression Recognition of Static and Dynamic Emotions](https://mlsanity.com/paper/2408.15777/) (2024)
- [Emotion Recognition under Consideration of the Emotion Component Process Model](https://mlsanity.com/paper/2107.12895/) (2021)
- [Visual Prompting in LLMs for Enhancing Emotion Recognition](https://mlsanity.com/paper/2410.02244/) (2024)
- [An Analysis of Emotion Communication Channels in Fan Fiction: Towards Emotional Storytelling](https://mlsanity.com/paper/1906.02402/) (2019)

## Built on by (most cited first, 2 of 2)

- [Do Emotions Influence Moral Judgment in Large Language Models?](https://mlsanity.com/paper/2604.19125/) (2026)
- [Emotional Labor Strategy Preferences in LLM Personas](https://mlsanity.com/paper/2609.00310/) (2026)

## Abstract (arXiv)

The embodiment of emotional reactions from body parts contains rich information about our affective experiences. We propose a framework that utilizes state-of-the-art large vision-language models (LVLMs) to generate Embodied LVLM Emotion Narratives (ELENA). These are well-defined, multi-layered text outputs, primarily comprising descriptions that focus on the salient body parts involved in emotional reactions. We also employ attention maps and observe that contemporary models exhibit a persistent bias towards the facial region. Despite this limitation, we observe that our employed framework can effectively recognize embodied emotions in face-masked images, outperforming baselines without any fine-tuning. ELENA opens a new trajectory for embodied emotion analysis across the modality of vision and enriches modeling in an affect-aware setting.