EG-VQA: Benchmarking Verifiable Video Question Answering with Grounded Temporal Evidence
The EG-VQA benchmark requires video models to generate both answers and supporting temporal evidence for questions, addressing a gap where existing VideoQA systems lack evidence grounding. The proposed EG-Reasoner model uses explicit supervision to learn this joint task, showing that structured evidence supervision is crucial for reliable and interpretable video reasoning.