33 citations · 126 across the 24 of their papers we have counts for
4 papers · 1 filter
Syntax-Enhanced Pre-trained Model
Zenan Xu, Daya Guo, Duyu Tang +7
We study the problem of leveraging the syntactic structure of text to enhance pre-trained models such as BERT and RoBERTa. Existing methods utilize syntax of text either in the pre…
Embedding Dynamic Attributed Networks by Modeling the Evolution Processes
Zenan Xu, Zijing Ou, Qinliang Su +3
Network embedding has recently emerged as a promising technique to embed nodes of a network into low-dimensional vectors. While fairly successful, most existing works focus on the…
Generative Semantic Hashing Enhanced via Boltzmann Machines
Lin Zheng, Qinliang Su, Dinghan Shen +1
Generative semantic hashing is a promising technique for large-scale information retrieval thanks to its fast retrieval speed and small memory footprint. For the tractability of tr…
Improve Variational Autoencoder for Text Generationwith Discrete Latent Bottleneck
Yang Zhao, Ping Yu, Suchismit Mahapatra +2
Variational autoencoders (VAEs) are essential tools in end-to-end representation learning. However, the sequential text generation common pitfall with VAEs is that the model tends…