Update README.md

README.md

@@ -14,9 +14,24 @@ size_categories:
 FL Benchmark originally proposed in [FedDAT](https://arxiv.org/abs/2308.12305), and modified by ourselves, splitting each dataset into different subtasks for task incremental learning setup in [FedMosaic (ICLR 2026)](https://openreview.net/forum?id=0g5Dk4Qfh0).
 Please checkout configuration of HFLB in the [paper](https://openreview.net/forum?id=0g5Dk4Qfh0)
 
-## Dataset Credits & References
+### Constituent Datasets
+| Dataset | Task Type | Reference |
+|---|---|---|
+| GQA | Compositional visual reasoning | Hudson & Manning, CVPR 2019 |
+| Abstract VQA | Abstract-scene visual question answering | Antol et al., ICCV 2015 |
+| SNLI-VE | Visual entailment | Xie et al., arXiv 2019 |
+| COCO-QA | Image question answering | Ren et al., NeurIPS 2015 |
+| NLVR2 | Natural-language visual reasoning over image pairs | Suhr et al., ACL 2019 |
+| VizWiz | Accessibility-focused VQA | Gurari et al., CVPR 2018 |
+| NLVR2 | Dual-image visual reasoning | Suhr et al., ACL 2019 |
+| AQUA | Art-domain visual question answering | Garcia et al., ECCV Workshops 2020 |
 
-DRAKE builds on the following publicly available datasets. **Please cite the original works** when using DRAKE in your research:
+---
+
+<details>
+<summary>Dataset Credits & References</summary>
+
+HFLB builds on the following publicly available datasets.
 
 ```bibtex
 @inproceedings{hudson2019gqa,
@@ -26,13 +41,50 @@ DRAKE builds on the following publicly available datasets. **Please cite the ori
   year      = {2019}
 }
 
+@inproceedings{antol2015vqa,
+  title     = {VQA: Visual Question Answering},
+  author    = {Antol, Stanislaw and Agrawal, Aishwarya and Lu, Jiasen and Mitchell, Margaret and Batra, Dhruv and Zitnick, C. Lawrence and Parikh, Devi},
+  booktitle = {ICCV},
+  year      = {2015}
+}
+
+@article{xie2019snlive,
+  title   = {Visual Entailment: A Novel Task for Fine-Grained Image Understanding},
+  author  = {Xie, Ning and Lai, Farley and Doran, Derek and Kadav, Asim},
+  journal = {arXiv preprint arXiv:1901.06706},
+  year    = {2019}
+}
+
+@inproceedings{ren2015cocoqa,
+  title     = {Exploring Models and Data for Image Question Answering},
+  author    = {Ren, Mengye and Kiros, Ryan and Zemel, Richard S.},
+  booktitle = {NeurIPS},
+  year      = {2015}
+}
+
+@inproceedings{suhr2019nlvr2,
+  title     = {A Corpus for Reasoning about Natural Language Grounded in Photographs},
+  author    = {Suhr, Alane and Zhou, Stephanie and Zhang, Ally and Zhang, Iris and Bai, Huajun and Artzi, Yoav},
+  booktitle = {ACL},
+  year      = {2019}
+}
+
 @inproceedings{gurari2018vizwiz,
   title     = {VizWiz Grand Challenge: Answering Visual Questions from Blind People},
   author    = {Gurari, Danna and Li, Qing and Stangl, Abigale J. and Guo, Anhong and Lin, Chi and Grauman, Kristen and Luo, Jiebo and Bigham, Jeffrey P.},
   booktitle = {CVPR},
   year      = {2018}
 }
+
+@inproceedings{garcia2020aqua,
+  title     = {A Dataset and Baselines for Visual Question Answering on Art},
+  author    = {Garcia, Noa and Ye, Chentao and Liu, Zihua and Hu, Qingtao and Otani, Mayu and Chu, Chenhui and Nakashima, Yuta and Mitamura, Teruko},
+  booktitle = {ECCV Workshops},
+  year      = {2020}
+}
 ```
+</details>
+---
 
 ## Citation