activity
20182022
most citedImproving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data

24 citations · 44 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CL20224 cited

SimKGC: Simple Contrastive Knowledge Graph Completion with Pre-trained Language Models

Liang Wang, Wei Zhao, Zhuoyu Wei +1

Knowledge graph completion (KGC) aims to reason over known facts and infer the missing links. Text-based methods such as KGBERT (Yao et al., 2019) learn entity representations from…

cs.SE202216 cited

What Do They Capture? -- A Structural Analysis of Pre-Trained Language Models for Source Code

Yao Wan, Wei Zhao, Hongyu Zhang +3

Recently, many pre-trained language models for source code have been proposed to model the context of code and serve as a basis for downstream code intelligence tasks such as code…

cs.CL2019

Denoising based Sequence-to-Sequence Pre-training for Text Generation

Liang Wang, Wei Zhao, Ruoyu Jia +2

This paper presents a new sequence-to-sequence (seq2seq) pre-training method PoDA (Pre-training of Denoising Autoencoders), which learns representations suitable for text generatio…

cs.CL201924 cited

Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data

Wei Zhao, Liang Wang, Kewei Shen +2

Neural machine translation systems have become state-of-the-art approaches for Grammatical Error Correction (GEC) task. In this paper, we propose a copy-augmented architecture for…

cs.CL2018

Multi-Perspective Context Aggregation for Semi-supervised Cloze-style Reading Comprehension

Liang Wang, Sujian Li, Wei Zhao +4

Cloze-style reading comprehension has been a popular task for measuring the progress of natural language understanding in recent years. In this paper, we design a novel multi-persp…

cs.CL2018

Yuanfudao at SemEval-2018 Task 11: Three-way Attention and Relational Knowledge for Commonsense Machine Comprehension

Liang Wang, Meng Sun, Wei Zhao +2

This paper describes our system for SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge. We use Three-way Attentive Networks (TriAN) to model interactions betwe…