Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10M - 100M
ArXiv:
Tags:
multimodal
License:
| license: apache-2.0 | |
| dataset_info: | |
| features: | |
| - name: data_path | |
| sequence: string | |
| - name: generator | |
| dtype: string | |
| - name: question | |
| dtype: string | |
| - name: answer | |
| dtype: string | |
| - name: options | |
| sequence: string | |
| - name: metadata | |
| dtype: string | |
| splits: | |
| - name: dcs_sa | |
| num_bytes: 1192380951 | |
| num_examples: 2294572 | |
| - name: dcs_mc | |
| num_bytes: 1313184418 | |
| num_examples: 2294572 | |
| - name: dcm_sa_2_img | |
| num_bytes: 858402949 | |
| num_examples: 1400000 | |
| - name: dcm_mc_2_img | |
| num_bytes: 931128693 | |
| num_examples: 1400000 | |
| - name: dcm_sa_3_img | |
| num_bytes: 1167523949 | |
| num_examples: 1400000 | |
| - name: dcm_mc_3_img | |
| num_bytes: 1297530106 | |
| num_examples: 1400000 | |
| - name: dcm_sa_4_img | |
| num_bytes: 1435043372 | |
| num_examples: 1400000 | |
| - name: dcm_mc_4_img | |
| num_bytes: 1596677323 | |
| num_examples: 1400000 | |
| - name: vgs_sa | |
| num_bytes: 595577425 | |
| num_examples: 1537630 | |
| - name: vgs_mc | |
| num_bytes: 671343503 | |
| num_examples: 1537630 | |
| - name: vgm_sa_2_img | |
| num_bytes: 536078137 | |
| num_examples: 1400000 | |
| - name: vgm_mc_2_img | |
| num_bytes: 612895409 | |
| num_examples: 1400000 | |
| - name: vgm_sa_3_img | |
| num_bytes: 693450488 | |
| num_examples: 1400000 | |
| - name: vgm_mc_3_img | |
| num_bytes: 830159021 | |
| num_examples: 1400000 | |
| - name: vgm_sa_4_img | |
| num_bytes: 802710456 | |
| num_examples: 1400000 | |
| - name: vgm_mc_4_img | |
| num_bytes: 972149375 | |
| num_examples: 1400000 | |
| download_size: 5904415104 | |
| dataset_size: 15506235575 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: dcs_sa | |
| path: data/dcs_sa-* | |
| - split: dcs_mc | |
| path: data/dcs_mc-* | |
| - split: dcm_sa_2_img | |
| path: data/dcm_sa_2_img-* | |
| - split: dcm_mc_2_img | |
| path: data/dcm_mc_2_img-* | |
| - split: dcm_sa_3_img | |
| path: data/dcm_sa_3_img-* | |
| - split: dcm_mc_3_img | |
| path: data/dcm_mc_3_img-* | |
| - split: dcm_sa_4_img | |
| path: data/dcm_sa_4_img-* | |
| - split: dcm_mc_4_img | |
| path: data/dcm_mc_4_img-* | |
| - split: vgs_sa | |
| path: data/vgs_sa-* | |
| - split: vgs_mc | |
| path: data/vgs_mc-* | |
| - split: vgm_sa_2_img | |
| path: data/vgm_sa_2_img-* | |
| - split: vgm_mc_2_img | |
| path: data/vgm_mc_2_img-* | |
| - split: vgm_sa_3_img | |
| path: data/vgm_sa_3_img-* | |
| - split: vgm_mc_3_img | |
| path: data/vgm_mc_3_img-* | |
| - split: vgm_sa_4_img | |
| path: data/vgm_sa_4_img-* | |
| - split: vgm_mc_4_img | |
| path: data/vgm_mc_4_img-* | |
| task_categories: | |
| - question-answering | |
| language: | |
| - en | |
| tags: | |
| - multimodal | |
| size_categories: | |
| - 10M<n<100M | |
| <h1 align="center"> | |
| ProVision: Programmatically Scaling Vision-centric Instruction Data for Multimodal Language Models | |
| </h1> | |
| ProVision is an extendable data generation engine which produces instruction data for large multimodal language models (MLMs). | |
| In particular, it synthesizes instruction data via data generators (Python programs) and scene graphs rather than proprietary models. It also includes a scene graph generation pipeline consisting of various state-of-the-art models (eg, object detection model). Thus, one can generate instruction data for any given image by first generating the scene graph and then apply data generators. | |
| Provision supports generation of both single-image and multi-image instruction data. One can also extend the engine by adding new data generators. | |
| **You are currently viewing the ProVision-10M dataset.** | |
|  | |
| ## Dataset Details | |
| ### Dataset Sources | |
| - **Repository**: https://github.com/JieyuZ2/ProVision | |
| - **Paper:** | |
| - **Blog:** | |
| - **Source Data:** [Visual Genome](https://homes.cs.washington.edu/~ranjay/visualgenome/index.html)/[GQA](https://cs.stanford.edu/people/dorarad/gqa/about.html) and [DataComp](https://www.datacomp.ai/dcclip/index.html#home) | |
| ## Uses | |
| ### Direct Use | |
| <!-- This section describes suitable use cases for the dataset. --> | |
| ProVision-10M is designed to facilitate research in training multimodal language models. | |
| ### Out-of-Scope Use | |
| <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> | |
| ProVision-10M was built to make research into large multimodal models more accessible. Using | |
| the dataset to train models that ingest or generate personally identifying information (such | |
| as images of people’s faces and other sensitive content) as well as military applications are all inappropriate use cases of ProVision-10M. | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| ProVision-10M was created to demonstrate the potential of programmatically synthesizing instruction data for training multimodal language models. | |
| ### Source Data | |
| The dataset is built upon two data sources: | |
| - we use 74,289 images and scene graphs from Visual Genome（the GQA version） | |
| - we use 126,106 images from DataComp | |
| ### Dataset summary | |
| **We do not release the images, please download the images from their original sources (GQA/DataComp)** | |
| | Split | Size | Format | Description | | |
| | :------------| :------ | :------ | :---- | | |
| | vgs_sa | 1537630 | short answer | single-image instruction data based on Visual Genome | | |
| | vgs_mc | 1537630 | multiple choice | single-image instruction data based on Visual Genome | | |
| | vgm_sa_2_img | 1400000 | short answer | 2-image instruction data based on Visual Genome | | |
| | vgm_mc_2_img | 1400000 | multiple choice | 2-image instruction data based on Visual Genome | | |
| | vgm_sa_3_img | 1400000 | short answer | 3-image instruction data based on Visual Genome | | |
| | vgm_mc_3_img | 1400000 | multiple choice | 3-image instruction data based on Visual Genome | | |
| | vgm_sa_4_img | 1400000 | short answer | 4-image instruction data based on Visual Genome | | |
| | vgm_mc_4_img | 1400000 | multiple choice | 4-image instruction data based on Visual Genome | | |
| | dcs_sa | 2294572 | short answer | single-image instruction data based on DataComp images | | |
| | dcs_mc | 2294572 | multiple choice | single-image instruction data based on DataComp images | | |
| | dcm_sa_2_img | 1400000 | short answer | 2-image instruction data based on DataComp images | | |
| | dcm_mc_2_img | 1400000 | multiple choice | 2-image instruction data based on DataComp images | | |
| | dcm_sa_3_img | 1400000 | short answer | 3-image instruction data based on DataComp images | | |
| | dcm_mc_3_img | 1400000 | multiple choice | 3-image instruction data based on DataComp images | | |
| | dcm_sa_4_img | 1400000 | short answer | 4-image instruction data based on DataComp images | | |
| | dcm_mc_4_img | 1400000 | multiple choice | 4-image instruction data based on DataComp images | | |
| ## License | |
| We release ProVision-10M under a Apache License 2.0. | |
| ## Citation | |
| ``` | |
| ``` |