activity
20202022
most citedMultiscale Collaborative Deep Models for Neural Machine Translation

7 citations · 14 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CL20226 cited

SUN: Exploring Intrinsic Uncertainties in Text-to-SQL Parsers

Bowen Qin, Lihan Wang, Binyuan Hui +7

This paper aims to improve the performance of text-to-SQL parsing by exploring the intrinsic uncertainties in the neural network based approaches (called SUN). From the data uncert…

cs.CL2022

Learning to Generalize to More: Continuous Semantic Augmentation for Neural Machine Translation

Xiangpeng Wei, Heng Yu, Yue Hu +4

The principal task in supervised neural machine translation (NMT) is to learn to generate target sentences conditioned on the source inputs from a set of parallel sentence pairs, a…

cs.CL20211 cited

Know Deeper: Knowledge-Conversation Cyclic Utilization Mechanism for Open-domain Dialogue Generation

Yajing Sun, Yue Hu, Luxi Xing +2

End-to-End intelligent neural dialogue systems suffer from the problems of generating inconsistent and repetitive responses. Existing dialogue models pay attention to unilaterally…

cs.CL2020

Bi-directional Cognitive Thinking Network for Machine Reading Comprehension

Wei Peng, Yue Hu, Luxi Xing +4

We propose a novel Bi-directional Cognitive Knowledge Framework (BCKF) for reading comprehension from the perspective of complementary learning systems theory. It aims to simulate…

cs.CL2020

Uncertainty-Aware Semantic Augmentation for Neural Machine Translation

Xiangpeng Wei, Heng Yu, Yue Hu +3

As a sequence-to-sequence generation task, neural machine translation (NMT) naturally contains intrinsic uncertainty, where a single sentence in one language has multiple valid cou…

cs.CL2020

On Learning Universal Representations Across Languages

Xiangpeng Wei, Rongxiang Weng, Yue Hu +3

Recent studies have demonstrated the overwhelming advantage of cross-lingual pre-trained models (PTMs), such as multilingual BERT and XLM, on cross-lingual NLP tasks. However, exis…