Create README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,56 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
task_categories:
|
| 3 |
+
- question-answering
|
| 4 |
+
language:
|
| 5 |
+
- en
|
| 6 |
+
tags:
|
| 7 |
+
- agent
|
| 8 |
+
size_categories:
|
| 9 |
+
- 100K<n<1M
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
# HFLB (Heterogeneous Federated Learning Benchmark)
|
| 13 |
+
|
| 14 |
+
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).
|
| 15 |
+
Please checkout configuration of HFLB in the [paper](https://openreview.net/forum?id=0g5Dk4Qfh0)
|
| 16 |
+
|
| 17 |
+
## Dataset Credits & References
|
| 18 |
+
|
| 19 |
+
DRAKE builds on the following publicly available datasets. **Please cite the original works** when using DRAKE in your research:
|
| 20 |
+
|
| 21 |
+
```bibtex
|
| 22 |
+
@inproceedings{hudson2019gqa,
|
| 23 |
+
title = {GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering},
|
| 24 |
+
author = {Hudson, Drew A. and Manning, Christopher D.},
|
| 25 |
+
booktitle = {CVPR},
|
| 26 |
+
year = {2019}
|
| 27 |
+
}
|
| 28 |
+
|
| 29 |
+
@inproceedings{gurari2018vizwiz,
|
| 30 |
+
title = {VizWiz Grand Challenge: Answering Visual Questions from Blind People},
|
| 31 |
+
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.},
|
| 32 |
+
booktitle = {CVPR},
|
| 33 |
+
year = {2018}
|
| 34 |
+
}
|
| 35 |
+
```
|
| 36 |
+
|
| 37 |
+
## Citation
|
| 38 |
+
|
| 39 |
+
If you use HFLB in your research, please cite FedDAT paper and our paper:
|
| 40 |
+
|
| 41 |
+
```bibtex
|
| 42 |
+
@inproceedings{chen2023feddat,
|
| 43 |
+
title={FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning},
|
| 44 |
+
author={Chen, Haokun and Zhang, Yao and Krompass, Denis and Gu, Jindong and Tresp, Volker},
|
| 45 |
+
booktitle={AAAI},
|
| 46 |
+
year={2024}
|
| 47 |
+
}
|
| 48 |
+
|
| 49 |
+
@inproceedings{seo2026colora,
|
| 50 |
+
title = {Co-LoRA: Collaborative Model Personalization on Heterogeneous Multi-Modal Clients},
|
| 51 |
+
author = {Seo, Minhyuk and Kim, Taeheon and Lee, Hankook and Choi, Jonghyun and Tuytelaars, Tinne},
|
| 52 |
+
booktitle = {The Fourteenth International Conference on Learning Representations (ICLR)},
|
| 53 |
+
year = {2026},
|
| 54 |
+
url = {https://openreview.net/forum?id=0g5Dk4Qfh0}
|
| 55 |
+
}
|
| 56 |
+
```
|