--- license: mit --- # Visual Haystacks Dataset Card ## Dataset details 1. Dataset type: Visual Haystacks (VHs) is a benchmark dataset specifically designed to evaluate the Large Multimodal Model's (LMM's) capability to handle long-context visual information. It can also be viewed as the first vision-centric Needle-In-A-Haystack (NIAH) benchmark dataset. Please also download COCO-2017's training set validation set. 2. Data Preparation and Benchmarking - Download the VQA questions: ``` huggingface-cli download --repo-type dataset tsunghanwu/visual_haystacks --local-dir dataset/VHs_qa ``` - Download the COCO 2017 dataset and organize it as follows, with the default root directory ./dataset/coco: ``` dataset/ ├── coco │ ├── annotations │ ├── test2017 │ └── val2017 └── VHs_qa ├── single_needle │ ├── VHs_large │ └── VHs_small └── multi_needle ├── multi_needle_2 └── multi_needle_3 ``` - Follow the instructions in https://github.com/visual-haystacks/vhs_benchmark to run the evaluation 3. Please check out our [project page](https://visual-haystacks.github.io) for more information. You can also send questions or comments about the model to [our github repo](https://github.com/visual-haystacks/vhs_benchmark/issues) ## Intended use Primary intended uses: The primary use of VHs is research on large multimodal models and chatbots. Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.