2.3k citations · 3.5k across the 28 of their papers we have counts for
7 papers · 1 filter
Benchmarking Multimodal AutoML for Tabular Data with Text Fields
Xingjian Shi, Jonas Mueller, Nick Erickson +2
We consider the use of automated supervised learning systems for data tables that not only contain numeric/categorical columns, but one or more text fields as well. Here we assembl…
Blending Anti-Aliasing into Vision Transformer
Shengju Qian, Hao Shao, Yi Zhu +2
The transformer architectures, based on self-attention mechanism and convolution-free design, recently found superior performance and booming applications in computer vision. Howev…
Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing
Haoyu He, Xingjian Shi, Jonas Mueller +3
We aim to identify how different components in the KD pipeline affect the resulting performance and how much the optimal KD pipeline varies across different datasets/tasks, such as…
Progressive Coordinate Transforms for Monocular 3D Object Detection
Li Wang, Li Zhang, Yi Zhu +4
Recognizing and localizing objects in the 3D space is a crucial ability for an AI agent to perceive its surrounding environment. While significant progress has been achieved with e…
Video Contrastive Learning with Global Context
Haofei Kuang, Yi Zhu, Zhi Zhang +5
Contrastive learning has revolutionized self-supervised image representation learning field, and recently been adapted to video domain. One of the greatest advantages of contrastiv…
A Unified Efficient Pyramid Transformer for Semantic Segmentation
Fangrui Zhu, Yi Zhu, Li Zhang +3
Semantic segmentation is a challenging problem due to difficulties in modeling context in complex scenes and class confusions along boundaries. Most literature either focuses on co…
CrossNorm and SelfNorm for Generalization under Distribution Shifts
Zhiqiang Tang, Yunhe Gao, Yi Zhu +3
Traditional normalization techniques (e.g., Batch Normalization and Instance Normalization) generally and simplistically assume that training and test data follow the same distribu…