VQA Benchmark

Visual Question Answering (VQA) benchmarks evaluate the ability of artificial intelligence models to understand and respond to questions about images. Current research focuses on improving model robustness to variations in question phrasing and answer formats, enhancing reasoning capabilities through retrieval-augmented architectures and modular designs, and addressing biases stemming from language priors. These advancements aim to create more reliable and explainable VQA systems, impacting fields like healthcare (through analysis of medical images) and remote sensing (by enabling efficient image interpretation), while also furthering our understanding of multimodal learning.