| # Upstream attribution and modifications |
|
|
| License sources checked on **2026-09-28**. License texts and download URLs are |
| recorded in `licenses/`; pinned construction resources are recorded in |
| `protocol/source-resources.json`. |
|
|
| **PlotQA: Reasoning over Scientific Plots** — Nitesh Methani, Pritha Ganguly, |
| Mitesh M. Khapra, and Pratyush Kumar, WACV 2020. |
| [Official dataset/code license statement](https://github.com/NiteshMethani/PlotQA#license) |
| and [pinned source instructions](https://github.com/NiteshMethani/PlotQA/blob/e0f5c34acbe92753f70798aafda99184e3e0cd8c/PlotQA_Dataset.md). |
| Dataset: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). |
| The construction used the pinned |
| [Dodon mirror](https://huggingface.co/datasets/Dodon/plotqa-dataset/tree/6e97b674c6afcc28f79b90108e4d736b08bb2966) |
| as a transport source, retaining official upstream terms. Charts are re-rendered |
| from source tables; target values, visibility and referents are changed under |
| explicit programs while question text is preserved. The official PlotQA paper |
| describes source data collected from real-world organizations; this package |
| does not assert ownership of those underlying facts or additional third-party |
| rights. Numeric table provenance remains in the per-world metadata. |
|
|
| **CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual |
| Reasoning** — Justin Johnson, Bharath Hariharan, Laurens van der Maaten, |
| Li Fei-Fei, C. Lawrence Zitnick, and Ross Girshick, CVPR 2017. |
| [Official data and license statement](https://cs.stanford.edu/people/jcjohns/clevr/). |
| Dataset: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). |
| [Official generator](https://github.com/facebookresearch/clevr-dataset-gen/tree/f0ce2c81750bfae09b5bf94d009f42e055f2cb3a). |
| Scenes are freshly rendered with the official Blender 2.79b/Cycles assets, with |
| source-program attribute changes and object visibility interventions. New label |
| and edit evidence is supplied separately from the upstream data. |
|
|
| **GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question |
| Answering** — Drew A. Hudson and Christopher D. Manning, CVPR 2019. |
| [Official source downloads](https://cs.stanford.edu/people/dorarad/gqa/download.html) |
| and [official question-generator repository](https://github.com/dorarad/gqa). |
| No explicit annotation redistribution grant was located on these pages or in |
| the downloaded `questions1.2.zip` and `sceneGraphs.zip` README files. The public |
| candidate uses source references and local reconstruction. The reconstruction |
| normalizes source JPEGs and applies constant gray patches at source object |
| boxes; symbolic world edits and source-program alternatives support its labels. |
|
|
| **Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image |
| Annotations** — Ranjay Krishna and collaborators, IJCV 2017. |
| [Official data page](https://homes.cs.washington.edu/~ranjay/visualgenome/api.html) |
| links [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). |
| This is the source of GQA photographs and the basis of its scene annotations. |
| Visual Genome's notice is retained as provenance, not used to infer a license |
| for all GQA-authored annotations. No photographs are bundled in this candidate. |
|
|
| The project software is the Explicit Learning project (2026), Apache 2.0 as |
| declared by its package metadata. The dataset release and documentation are |
| prepared by Sungguk Cha, Mintae Kim, Youngsub Han, Byoung-Ki Jeon, and Sangyeob |
| Lee, using the manuscript author list. No upstream author endorses these edits |
| or the reported model results by virtue of this attribution. |
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