license: apache-2.0
task_categories:
- video-text-to-text
V-NIAH-D Benchmark
A Visual Needle-In-A-Haystack Benchmark with Periodic Distractors. It was presented in VideoRoPE: What Makes for Good Video Rotary Position Embedding?.
One can use it by following steps similar to V-NIAH.
VideoRoPE Training Data
To facilitate the reproduction of our experimental results, we have also uploaded the data used by VideoRoPE. We use a subset of the LLaVA-Video-178K dataset to train VideoRoPE.
The LLaVA-Video-178K dataset consists of 178K videos and approximately 5 million question-answer (QA) pairs from diverse sources such as HD-VILA, Kinetics, and ActivityNet. To balance training efficiency and long-video comprehension, we randomly select 136K videos with durations under 2 minutes and 18K videos with durations between 2 and 3 minutes. This process resulted in our training set containing approximately 1.3 million pairs.