The ProMQA dataset, introduced in recent research published on arXiv, represents a significant advancement in the evaluation of multimodal systems designed for procedural activity understanding. Unlike traditional datasets that primarily focus on classification tasks, ProMQA emphasizes real-world applications where such systems assist users in effectively following instructions. This shift in focus aims to better capture the complexities involved in procedural tasks by integrating multiple modalities, thereby enhancing the practical utility of AI models. The dataset’s design reflects an effort to move beyond conventional benchmarks, addressing the need for more comprehensive evaluation tools in multimodal question answering. By targeting procedural activities, ProMQA provides a platform for testing AI systems in scenarios that closely mirror everyday user interactions. This approach aligns with ongoing developments in AI research that prioritize usability and real-world applicability. Overall, ProMQA contributes to the growing body of resources aimed at improving the interpretability and functionality of multimodal AI systems.