112 citations · 444 across the 29 of their papers we have counts for
9 papers · 1 filter
Modeling Token-level Uncertainty to Learn Unknown Concepts in SLU via Calibrated Dirichlet Prior RNN
Yilin Shen, Wenhu Chen, Hongxia Jin
One major task of spoken language understanding (SLU) in modern personal assistants is to extract semantic concepts from an utterance, called slot filling. Although existing slot f…
KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation
Wenhu Chen, Yu Su, Xifeng Yan +1
Data-to-text generation has recently attracted substantial interests due to its wide applications. Existing methods have shown impressive performance on an array of tasks. However,…
Unsupervised Multi-hop Question Answering by Question Generation
Liangming Pan, Wenhu Chen, Wenhan Xiong +2
Obtaining training data for multi-hop question answering (QA) is time-consuming and resource-intensive. We explore the possibility to train a well-performed multi-hop QA model with…
Open Question Answering over Tables and Text
Wenhu Chen, Ming-Wei Chang, Eva Schlinger +2
In open question answering (QA), the answer to a question is produced by retrieving and then analyzing documents that might contain answers to the question. Most open QA systems ha…
Logical Natural Language Generation from Open-Domain Tables
Wenhu Chen, Jianshu Chen, Yu Su +2
Neural natural language generation (NLG) models have recently shown remarkable progress in fluency and coherence. However, existing studies on neural NLG are primarily focused on s…
Logic2Text: High-Fidelity Natural Language Generation from Logical Forms
Zhiyu Chen, Wenhu Chen, Hanwen Zha +4
Previous works on Natural Language Generation (NLG) from structured data have primarily focused on surface-level descriptions of record sequences. However, for complex structured d…