116 citations · 135 across the 5 of their papers we have counts for
7 papers
On the Encoder-Decoder Incompatibility in Variational Text Modeling and Beyond
Chen Wu, Prince Zizhuang Wang, William Yang Wang
Variational autoencoders (VAEs) combine latent variables with amortized variational inference, whose optimization usually converges into a trivial local optimum termed posterior co…
HULK: An Energy Efficiency Benchmark Platform for Responsible Natural Language Processing
Xiyou Zhou, Zhiyu Chen, Xiaoyong Jin +1
Computation-intensive pretrained models have been taking the lead of many natural language processing benchmarks such as GLUE. However, energy efficiency in the process of model tr…
Table-to-Text Natural Language Generation with Unseen Schemas
Tianyu Liu, Wei Wei, William Yang Wang
Traditional table-to-text natural language generation (NLG) tasks focus on generating text from schemas that are already seen in the training set. This limitation curbs their gener…
r/Fakeddit: A New Multimodal Benchmark Dataset for Fine-grained Fake News Detection
Kai Nakamura, Sharon Levy, William Yang Wang
Fake news has altered society in negative ways in politics and culture. It has adversely affected both online social network systems as well as offline communities and conversation…
Fine-tune Bert for DocRED with Two-step Process
Hong Wang, Christfried Focke, Rob Sylvester +2
Modelling relations between multiple entities has attracted increasing attention recently, and a new dataset called DocRED has been collected in order to accelerate the research on…
How Large a Vocabulary Does Text Classification Need? A Variational Approach to Vocabulary Selection
Wenhu Chen, Yu Su, Yilin Shen +3
With the rapid development in deep learning, deep neural networks have been widely adopted in many real-life natural language applications. Under deep neural networks, a pre-define…