arXiv cs.AI
· Papers
EG-VQA: Benchmarking Verifiable Video Question Answering with Grounded Temporal Evidence
arXiv:2606.24797v1 Announce Type: cross Abstract: Recent advances in Video Large Language Models (Video-LLMs) have yielded promising performance on video question answering (VideoQA). Nevertheless, existing benchmarks are predominantly evaluated through answer correctness, while the grounding of predictions in relevant