268 citations · 771 across the 18 of their papers we have counts for
38 papers
SYNERGY: Building Task Bots at Scale Using Symbolic Knowledge and Machine Teaching
Baolin Peng, Chunyuan Li, Zhu Zhang +3
In this paper we explore the use of symbolic knowledge and machine teaching to reduce human data labeling efforts in building neural task bots. We propose SYNERGY, a hybrid learnin…
Focal Self-attention for Local-Global Interactions in Vision Transformers
Jianwei Yang, Chunyuan Li, Pengchuan Zhang +4
Recently, Vision Transformer and its variants have shown great promise on various computer vision tasks. The ability of capturing short- and long-range visual dependencies through…
Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation
Jinyu Yang, Chunyuan Li, Weizhi An +5
Recent studies imply that deep neural networks are vulnerable to adversarial examples -- inputs with a slight but intentional perturbation are incorrectly classified by the network…
Partition-Guided GANs
Mohammadreza Armandpour, Ali Sadeghian, Chunyuan Li +1
Despite the success of Generative Adversarial Networks (GANs), their training suffers from several well-known problems, including mode collapse and difficulties learning a disconne…
Self-supervised Pre-training with Hard Examples Improves Visual Representations
Chunyuan Li, Xiujun Li, Lei Zhang +3
Self-supervised pre-training (SSP) employs random image transformations to generate training data for visual representation learning. In this paper, we first present a modeling fra…
SDA: Improving Text Generation with Self Data Augmentation
Ping Yu, Ruiyi Zhang, Yang Zhao +3
Data augmentation has been widely used to improve deep neural networks in many research fields, such as computer vision. However, less work has been done in the context of text, pa…