24 citations · 46 across the 7 of their papers we have counts for
7 papers
Switchable Decision: Dynamic Neural Generation Networks
Shujian Zhang, Korawat Tanwisuth, Chengyue Gong +2
Auto-regressive generation models achieve competitive performance across many different NLP tasks such as summarization, question answering, and classifications. However, they are…
POUF: Prompt-oriented unsupervised fine-tuning for large pre-trained models
Korawat Tanwisuth, Shujian Zhang, Huangjie Zheng +2
Through prompting, large-scale pre-trained models have become more expressive and powerful, gaining significant attention in recent years. Though these big models have zero-shot ca…
A Prototype-Oriented Clustering for Domain Shift with Source Privacy
Korawat Tanwisuth, Shujian Zhang, Pengcheng He +1
Unsupervised clustering under domain shift (UCDS) studies how to transfer the knowledge from abundant unlabeled data from multiple source domains to learn the representation of the…
Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings
Dongsheng Wang, Dandan Guo, He Zhao +4
A topic model is often formulated as a generative model that explains how each word of a document is generated given a set of topics and document-specific topic proportions. It is…
Alignment Attention by Matching Key and Query Distributions
Shujian Zhang, Xinjie Fan, Huangjie Zheng +2
The neural attention mechanism has been incorporated into deep neural networks to achieve state-of-the-art performance in various domains. Most such models use multi-head self-atte…
A Prototype-Oriented Framework for Unsupervised Domain Adaptation
Korawat Tanwisuth, Xinjie Fan, Huangjie Zheng +4
Existing methods for unsupervised domain adaptation often rely on minimizing some statistical distance between the source and target samples in the latent space. To avoid the sampl…
Contextual Dropout: An Efficient Sample-Dependent Dropout Module
Xinjie Fan, Shujian Zhang, Korawat Tanwisuth +2
Dropout has been demonstrated as a simple and effective module to not only regularize the training process of deep neural networks, but also provide the uncertainty estimation for…