4 papers
Coarse-Grained Boltzmann Generators
Weilong Chen, Bojun Zhao, Jan Eckwert +1
Sampling equilibrium molecular configurations from the Boltzmann distribution is a longstanding challenge. Boltzmann Generators (BGs) address this by combining exact-likelihood gen…
DD-Ranking: Rethinking the Evaluation of Dataset Distillation
Zekai Li, Xinhao Zhong, Samir Khaki +49
In recent years, dataset distillation has provided a reliable solution for data compression, where models trained on the resulting smaller synthetic datasets achieve performance co…
Image Captions are Natural Prompts for Text-to-Image Models
Shiye Lei, Hao Chen, Sen Zhang +2
With the rapid development of Artificial Intelligence Generated Content (AIGC), it has become a common practice to train models on synthetic data due to data-scarcity and privacy l…
Enhancing Generalization via Sharpness-Aware Trajectory Matching for Dataset Condensation
Boyan Gao, Bo Zhao, Shreyank N Gowda +4
Dataset condensation aims to synthesize datasets with a few representative samples that can effectively represent the original datasets. This enables efficient training and produce…