20 citations · 86 across the 17 of their papers we have counts for
17 papers
Collaborative Knowledge Graph Fusion by Exploiting the Open Corpus
Yue Wang, Yao Wan, Lu Bai +5
To alleviate the challenges of building Knowledge Graphs (KG) from scratch, a more general task is to enrich a KG using triples from an open corpus, where the obtained triples cont…
Attend, Memorize and Generate: Towards Faithful Table-to-Text Generation in Few Shots
Wenting Zhao, Ye Liu, Yao Wan +1
Few-shot table-to-text generation is a task of composing fluent and faithful sentences to convey table content using limited data. Despite many efforts having been made towards gen…
DANets: Deep Abstract Networks for Tabular Data Classification and Regression
Jintai Chen, Kuanlun Liao, Yao Wan +2
Tabular data are ubiquitous in real world applications. Although many commonly-used neural components (e.g., convolution) and extensible neural networks (e.g., ResNet) have been de…
HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization
Ye Liu, Jian-Guo Zhang, Yao Wan +3
To capture the semantic graph structure from raw text, most existing summarization approaches are built on GNNs with a pre-trained model. However, these methods suffer from cumbers…
Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection
Jianguo Zhang, Kazuma Hashimoto, Yao Wan +4
Pre-trained Transformer-based models were reported to be robust in intent classification. In this work, we first point out the importance of in-domain out-of-scope detection in few…
Enriching Non-Autoregressive Transformer with Syntactic and SemanticStructures for Neural Machine Translation
Ye Liu, Yao Wan, Jian-Guo Zhang +2
The non-autoregressive models have boosted the efficiency of neural machine translation through parallelized decoding at the cost of effectiveness when comparing with the autoregre…