EMMA Multimodal Reasoning Benchmark Dataset

EMMA (Enhanced MultiModal reAsoning) is a multimodal reasoning benchmark dataset released in 2025 by a research team from the University of Electronic Science and Technology of China, Sun Yat-sen University, University of Washington, and Microsoft. The relevant paper results are:Can MLLMs Reason in Multimodality? EMMA: An Enhanced MultiModal ReAsoning Benchmark", which aims to provide a standardized testing platform for evaluating the complex reasoning capabilities of multimodal large models (MLLMs).

The dataset focuses on multimodal reasoning tasks in the fields of organic chemistry (42%), mathematics (32%), physics (6%), and programming (20%). It contains 2,788 questions, of which 1,796 are newly constructed samples. It supports fine-grained task division and aims to promote the joint understanding of images and texts. The data task types include chemical reaction simulation, mathematical graphic reasoning, physical path tracing, programming visualization, etc.