# MER 2025: When Affective Computing Meets Large Language Models

arXiv: https://arxiv.org/abs/2504.19423 · HTML: https://mlsanity.com/paper/2504.19423/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Apr 2025.

## Built on by (most cited first, 10 of 10)

- [AVERE: Improving Audiovisual Emotion Reasoning with Preference Optimization](https://mlsanity.com/paper/2602.07054/) (2026)
- [UDDETTS: Unifying Discrete and Dimensional Emotions for Controllable Emotional Text-to-Speech](https://mlsanity.com/paper/2505.10599/) (2025)
- [XEmoGPT: An Explainable Multimodal Emotion Recognition Framework with Cue-Level Perception and Reasoning](https://mlsanity.com/paper/2602.05496/) (2026)
- [Style over Substance: A Shortcut Audit of Emotion-Description Preference Evaluation](https://mlsanity.com/paper/2607.18508/) (2026)
- [Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis](https://mlsanity.com/paper/2506.07148/) (2025)
- [QASA: Quality-Aware Semantic Augmentation for Robust Multimodal Sentiment Analysis](https://mlsanity.com/paper/2601.06870/) (2026)
- [Integrating Fine-Grained Audio-Visual Evidence for Robust Multimodal Emotion Reasoning](https://mlsanity.com/paper/2601.18321/) (2026)
- [Modeling Induced Pleasure through Cognitive Appraisal Prediction via Multimodal Fusion](https://mlsanity.com/paper/2604.23753/) (2026)
- [FAIR_XAI: Improving Multimodal Foundation Model Fairness via Explainability for Wellbeing Assessment](https://mlsanity.com/paper/2604.23786/) (2026)
- [RobotEQ-Video: A Video-Centric Benchmark for Social Proactive Intelligence with World-State Taxonomy](https://mlsanity.com/paper/2609.21371/) (2026)

## Abstract (arXiv)

MER2025 is the third year of our MER series of challenges, aiming to bring together researchers in the affective computing community to explore emerging trends and future directions in the field. Previously, MER2023 focused on multi-label learning, noise robustness, and semi-supervised learning, while MER2024 introduced a new track dedicated to open-vocabulary emotion recognition. This year, MER2025 centers on the theme "When Affective Computing Meets Large Language Models (LLMs)".We aim to shift the paradigm from traditional categorical frameworks reliant on predefined emotion taxonomies to LLM-driven generative methods, offering innovative solutions for more accurate and reliable emotion understanding. The challenge features four tracks: MER-SEMI focuses on fixed categorical emotion recognition enhanced by semi-supervised learning; MER-FG explores fine-grained emotions, expanding recognition from basic to nuanced emotional states; MER-DES incorporates multimodal cues (beyond emotion words) into predictions to enhance model interpretability; MER-PR investigates whether emotion prediction results can improve personality recognition performance. For the first three tracks, baseline code is available at MERTools, and datasets can be accessed via Hugging Face. For the last track, the dataset and baseline code are available on GitHub.