ScienceQA-IMG

<p align="center" width="100%"> <img src="https://i.postimg.cc/g0QRgMVv/WX20240228-113337-2x.png" width="100%" height="80%"> </p> # Large-scale Multi-modality Models Evaluation Suite > Accelerating the development of large-scale multi-modality models (LMMs) with `lmms-eval` 🏠 [Homepage](https://lmms-lab.github.io/) | 📚 [Documentation](docs/README.md) | 🤗 [Huggingface Datasets](https://huggingface.co/lmms-lab) # This Dataset This is a formatted and filtered version of [derek-thomas/ScienceQA](https://huggingface.co/datasets/derek-thomas/ScienceQA) with only image instances. It is used in our `lmms-eval` pipeline to allow for one-click evaluations of large multi-modality models. ``` @inproceedings{lu2022learn, title={Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering}, author={Lu, Pan and Mishra, Swaroop and Xia, Tony and Qiu, Liang and Chang, Kai-Wei and Zhu, Song-Chun and Tafjord, Oyvind and Clark, Peter and Ashwin Kalyan}, booktitle={The 36th Conference on Neural Information Processing Systems (NeurIPS)}, year={2022} } ```<p align="center" width="100%"> <img src="https://i.postimg.cc/g0QRgMVv/WX20240228-113337-2x.png" width="100%" height="80%"> </p> # 大规模多模态模型评测套件 > 借助`lmms-eval`加速大规模多模态模型（Large-scale Multi-modality Models, LMMs）的研发 🏠 [主页](https://lmms-lab.github.io/) | 📚 [文档](docs/README.md) | 🤗 [Huggingface数据集](https://huggingface.co/lmms-lab) ## 本数据集 本数据集是[derek-thomas/ScienceQA](https://huggingface.co/datasets/derek-thomas/ScienceQA)的格式化与筛选版本，仅保留图像实例。我们将其应用于`lmms-eval`流水线中，以实现大规模多模态模型的一键式评测。 @inproceedings{lu2022learn, title={学会解释：面向科学问答的基于思维链的多模态推理}, author={Lu, Pan and Mishra, Swaroop and Xia, Tony and Qiu, Liang and Chang, Kai-Wei and Zhu, Song-Chun and Tafjord, Oyvind and Clark, Peter and Ashwin Kalyan}, booktitle={第36届神经信息处理系统大会（NeurIPS)}, year={2022} }

搜集汇总

背景与挑战

背景概述

ScienceQA-IMG是ScienceQA数据集的格式化过滤版本，专门包含图像实例，用于通过lmms-eval管道评估大规模多模态模型。它基于NeurIPS 2022的研究，采用Apache License 2.0许可证。