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

24 citations · 29 across the 3 of their papers we have counts for

collaborators

7 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.CL2020

Ape210K: A Large-Scale and Template-Rich Dataset of Math Word Problems

Wei Zhao, Mingyue Shang, Yang Liu +2

Automatic math word problem solving has attracted growing attention in recent years. The evaluation datasets used by previous works have serious limitations in terms of scale and d…

cs.CL20201 cited

Investigating Label Bias in Beam Search for Open-ended Text Generation

Liang Wang, Jinlong Liu, Jingming Liu

Beam search is an effective and widely used decoding algorithm in many sequence-to-sequence (seq2seq) text generation tasks. However, in open-ended text generation, beam search is…

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…