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20172023
most citedMulti-Task Deep Neural Networks for Natural Language Understanding

221 citations · 783 across the 39 of their papers we have counts for

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Showing 2019Show all

14 papers · 1 filter

cs.CL2019

RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers

Bailin Wang, Richard Shin, Xiaodong Liu +2

When translating natural language questions into SQL queries to answer questions from a database, contemporary semantic parsing models struggle to generalize to unseen database sch…

cs.CL2019

SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization

Haoming Jiang, Pengcheng He, Weizhu Chen +3

Transfer learning has fundamentally changed the landscape of natural language processing (NLP) research. Many existing state-of-the-art models are first pre-trained on a large text…

eess.SP2019★ 1 cited

Performance Analysis on Visible Light Communications With Multi-Eavesdroppers and Practical Amplitude Constraint

Xiaodong Liu, Yuhao Wang, Fuhui Zhou +2

In this paper the secure performance for the visible light communication (VLC) system with multiple eavesdroppers is studied. By considering the practical amplitude constraint inst…

cs.CL2019

Adversarial Domain Adaptation for Machine Reading Comprehension

Huazheng Wang, Zhe Gan, Xiaodong Liu +3

In this paper, we focus on unsupervised domain adaptation for Machine Reading Comprehension (MRC), where the source domain has a large amount of labeled data, while only unlabeled…

cs.LG2019

The Learning of Fuzzy Cognitive Maps With Noisy Data: A Rapid and Robust Learning Method With Maximum Entropy

Guoliang Feng, Wei Lu, Witold Pedrycz +2

Numerous learning methods for fuzzy cognitive maps (FCMs), such as the Hebbian-based and the population-based learning methods, have been developed for modeling and simulating dyna…

cs.LG2019

On the Variance of the Adaptive Learning Rate and Beyond

Liyuan Liu, Haoming Jiang, Pengcheng He +4

The learning rate warmup heuristic achieves remarkable success in stabilizing training, accelerating convergence and improving generalization for adaptive stochastic optimization a…