ICLR 2025poster0 citations
GenDataAgent: On-the-fly Dataset Augmentation with Synthetic Data
Zhiteng Li, Lele Chen, Jerone Andrews, Yunhao Ba, Yulun Zhang, Alice Xiang
Abstract
We propose a generative agent that augments training datasets with synthetic data for model fine-tuning. Unlike prior work, which uniformly samples synthetic data, our agent iteratively generates relevant samples on-the-fly, aligning with the target distribution. It prioritizes synthetic data that complements difficult training samples, focusing on those with high variance in gradient updates. Experiments across several image classification tasks demonstrate the effectiveness of our approach.
supervised learningclassificationcomputer visionsynthetic datagenerative AIresponsible AIfairness
BibTeX
@inproceedings{
li2025gendataagent,
title={GenDataAgent: On-the-fly Dataset Augmentation with Synthetic Data},
author={Zhiteng Li and Lele Chen and Jerone Andrews and Yunhao Ba and Yulun Zhang and Alice Xiang},
booktitle={The Thirteenth International Conference on Learning Representations},
year={2025},
url={https://openreview.net/forum?id=WoGnnggVCZ}
}