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20162023
most citedPre-Training with Whole Word Masking for Chinese BERT

1.2k citations · 2.9k across the 87 of their papers we have counts for

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Showing 2022Show all

15 papers · 1 filter

cs.CL2022★ 1 cited

MultiSpider: Towards Benchmarking Multilingual Text-to-SQL Semantic Parsing

Longxu Dou, Yan Gao, Mingyang Pan +4

Text-to-SQL semantic parsing is an important NLP task, which greatly facilitates the interaction between users and the database and becomes the key component in many human-computer…

cs.CL2022★ 3 cited

A Survey on Table-and-Text HybridQA: Concepts, Methods, Challenges and Future Directions

Dingzirui Wang, Longxu Dou, Wanxiang Che

Table-and-text hybrid question answering (HybridQA) is a widely used and challenging NLP task commonly applied in the financial and scientific domain. The early research focuses on…

cs.CL2022★ 4 cited

A Survey on Natural Language Processing for Programming

Qingfu Zhu, Xianzhen Luo, Fang Liu +2

Natural language processing for programming aims to use NLP techniques to assist programming. It is increasingly prevalent for its effectiveness in improving productivity. Distinct…

cs.CL2022★ 26 cited

LERT: A Linguistically-motivated Pre-trained Language Model

Yiming Cui, Wanxiang Che, Shijin Wang +1

Pre-trained Language Model (PLM) has become a representative foundation model in the natural language processing field. Most PLMs are trained with linguistic-agnostic pre-training…

cs.CL2022★ 14 cited

MetaPrompting: Learning to Learn Better Prompts

Yutai Hou, Hongyuan Dong, Xinghao Wang +2

Prompting method is regarded as one of the crucial progress for few-shot nature language processing. Recent research on prompting moves from discrete tokens based ``hard prompts''…

cs.CL2022★ 2 cited

Overview of CTC 2021: Chinese Text Correction for Native Speakers

Honghong Zhao, Baoxin Wang, Dayong Wu +3

In this paper, we present an overview of the CTC 2021, a Chinese text correction task for native speakers. We give detailed descriptions of the task definition and the data for tra…