We propose Evidence-Backed Video Question Answering (E-VQA), a task where multimodal models are designed to jointly produce a semantic textual answer and associated spatiotemporal evidence. This evidence includes temporal segments and dense, tracked object segmentation masklets. A masklet is defined as a temporal sequence of object segmentation masks tracked over time.

Our model was fine-tuned from UniPixel, which is built upon QWen2.5-VL and SAM 2.1. UniPixel is a unified model designed to handle both video question answering and mask generation.

This was released for research purposes only, in support of the academic paper Evidence-Backed Video Question Answering.

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