10 citations · 27 across the 5 of their papers we have counts for
6 papers
Convolutions and Self-Attention: Re-interpreting Relative Positions in Pre-trained Language Models
Tyler A. Chang, Yifan Xu, Weijian Xu +1
In this paper, we detail the relationship between convolutions and self-attention in natural language tasks. We show that relative position embeddings in self-attention layers are…
Pose Recognition with Cascade Transformers
Ke Li, Shijie Wang, Xiang Zhang +3
In this paper, we present a regression-based pose recognition method using cascade Transformers. One way to categorize the existing approaches in this domain is to separate them in…
Co-Scale Conv-Attentional Image Transformers
Weijian Xu, Yifan Xu, Tyler Chang +1
In this paper, we present Co-scale conv-attentional image Transformers (CoaT), a Transformer-based image classifier equipped with co-scale and conv-attentional mechanisms. First, t…
Line Segment Detection Using Transformers without Edges
Yifan Xu, Weijian Xu, David Cheung +1
In this paper, we present a joint end-to-end line segment detection algorithm using Transformers that is post-processing and heuristics-guided intermediate processing (edge/junctio…
Guided Variational Autoencoder for Disentanglement Learning
Zheng Ding, Yifan Xu, Weijian Xu +4
We propose an algorithm, guided variational autoencoder (Guided-VAE), that is able to learn a controllable generative model by performing latent representation disentanglement lear…
Wasserstein Introspective Neural Networks
Kwonjoon Lee, Weijian Xu, Fan Fan +1
We present Wasserstein introspective neural networks (WINN) that are both a generator and a discriminator within a single model. WINN provides a significant improvement over the re…