1.9k citations · 2.7k across the 13 of their papers we have counts for
5 papers · 1 filter
Towards All-in-one Pre-training via Maximizing Multi-modal Mutual Information
Weijie Su, Xizhou Zhu, Chenxin Tao +7
To effectively exploit the potential of large-scale models, various pre-training strategies supported by massive data from different sources are proposed, including supervised pre-…
A Law of Data Separation in Deep Learning
Hangfeng He, Weijie J. Su
While deep learning has enabled significant advances in many areas of science, its black-box nature hinders architecture design for future artificial intelligence applications and…
FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data
Zhun Deng, Jiayao Zhang, Linjun Zhang +4
Algorithmic fairness plays an important role in machine learning and imposing fairness constraints during learning is a common approach. However, many datasets are imbalanced in ce…
Siamese Image Modeling for Self-Supervised Vision Representation Learning
Chenxin Tao, Xizhou Zhu, Weijie Su +6
Self-supervised learning (SSL) has delivered superior performance on a variety of downstream vision tasks. Two main-stream SSL frameworks have been proposed, i.e., Instance Discrim…
ROCK: Causal Inference Principles for Reasoning about Commonsense Causality
Jiayao Zhang, Hongming Zhang, Weijie J. Su +1
Commonsense causality reasoning (CCR) aims at identifying plausible causes and effects in natural language descriptions that are deemed reasonable by an average person. Although be…