activity
20162019
most citedERNIE: Enhanced Language Representation with Informative Entities

135 citations · 240 across the 5 of their papers we have counts for

collaborators

41 papers

cs.IR20202 cited

Knowledge Transfer via Pre-training for Recommendation: A Review and Prospect

Zheni Zeng, Chaojun Xiao, Yuan Yao +5

Recommender systems aim to provide item recommendations for users, and are usually faced with data sparsity problem (e.g., cold start) in real-world scenarios. Recently pre-trained…

cs.CL20209 cited

Learning to Attack: Towards Textual Adversarial Attacking in Real-world Situations

Yuan Zang, Bairu Hou, Fanchao Qi +3

Adversarial attacking aims to fool deep neural networks with adversarial examples. In the field of natural language processing, various textual adversarial attack models have been…

cs.CY202038 cited

Country Image in COVID-19 Pandemic: A Case Study of China

Huimin Chen, Zeyu Zhu, Fanchao Qi +4

Country image has a profound influence on international relations and economic development. In the worldwide outbreak of COVID-19, countries and their people display different reac…

cs.SD20201 cited

Robust Front-End for Multi-Channel ASR using Flow-Based Density Estimation

Hyeongju Kim, Hyeonseung Lee, Woo Hyun Kang +2

For multi-channel speech recognition, speech enhancement techniques such as denoising or dereverberation are conventionally applied as a front-end processor. Deep learning-based fr…

cs.CL202026 cited

How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence

Haoxi Zhong, Chaojun Xiao, Cunchao Tu +3

Legal Artificial Intelligence (LegalAI) focuses on applying the technology of artificial intelligence, especially natural language processing, to benefit tasks in the legal domain.…

cs.CL2020

Coreferential Reasoning Learning for Language Representation

Deming Ye, Yankai Lin, Jiaju Du +4

Language representation models such as BERT could effectively capture contextual semantic information from plain text, and have been proved to achieve promising results in lots of…