--- tags: - multimodal - emotion-recognition - emotional-intelligence - video - conversation language: - en license: apache-2.0 pretty_name: EmoBench-M task_categories: - video-classification - video-text-to-text dataset_info: - config: - config_name: default --- # EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models [![arXiv](https://img.shields.io/badge/arXiv-2502.04424-b31b1b.svg)](https://arxiv.org/abs/2502.04424) [![GitHub](https://img.shields.io/badge/GitHub-Emo--gml/EmoBench--M-blue?logo=github)](https://github.com/Emo-gml/EmoBench-M) ## Dataset Description **EmoBench-M** is a comprehensive benchmark designed to evaluate the Emotional Intelligence (EI) of Multimodal Large Language Models (MLLMs). It provides a challenging testbed for assessing a model's ability to understand and interpret human emotions from video, a critical step towards developing more empathetic and human-like AI systems. The dataset consists of video clips featuring individuals expressing various emotions. Each video is paired with a conversational prompt that asks the model to determine the emotion conveyed. This structure pushes models to integrate visual, auditory, and textual information to make a correct assessment, moving beyond simple text-based sentiment analysis. If you find this Dataset helpful, feel free to ⭐ it! [EmoBench-M](https://github.com/Emo-gml/EmoBench-M). ## 📦 Dataset Each JSON file contains conversation-style prompts and labels aligned with the corresponding video clips. The structure looks like: ```json [ { "id": "0", "video": "videos/ch-simsv2s/aqgy4_0004/00023.mp4", "conversations": [ { "from": "human", "value": "