H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 37 Citations 6,596 140 World Ranking 5303 National Ranking 496

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Natural language processing

Xipeng Qiu mainly focuses on Artificial intelligence, Natural language processing, Artificial neural network, Benchmark and Context. Xipeng Qiu undertakes interdisciplinary study in the fields of Artificial intelligence and Architecture through his works. The concepts of his Natural language processing study are interwoven with issues in Speech recognition and Transformer.

His work carried out in the field of Artificial neural network brings together such families of science as Feature engineering and Feature. His Context study deals with Word intersecting with Translation. His work is dedicated to discovering how Machine learning, Multi-task learning are connected with Training set and Variety and other disciplines.

His most cited work include:

  • Recurrent Neural Network for Text Classification with Multi-Task Learning (288 citations)
  • Adversarial Multi-task Learning for Text Classification (247 citations)
  • Long Short-Term Memory Neural Networks for Chinese Word Segmentation (184 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Artificial intelligence, Natural language processing, Machine learning, Artificial neural network and Segmentation. Many of his studies on Artificial intelligence involve topics that are commonly interrelated, such as Pattern recognition. He focuses mostly in the field of Pattern recognition, narrowing it down to topics relating to Pooling and, in certain cases, Task.

His studies in Natural language processing integrate themes in fields like Tree, Representation and Transformer. His Machine learning study integrates concerns from other disciplines, such as Multi-task learning, Training set, Adversarial system and Sequence labeling. The Artificial neural network study combines topics in areas such as Feature engineering and Benchmark.

He most often published in these fields:

  • Artificial intelligence (78.39%)
  • Natural language processing (46.23%)
  • Machine learning (19.60%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (78.39%)
  • Natural language processing (46.23%)
  • Automatic summarization (8.54%)

In recent papers he was focusing on the following fields of study:

Xipeng Qiu spends much of his time researching Artificial intelligence, Natural language processing, Automatic summarization, Machine learning and Transformer. Artificial intelligence is represented through his Language model, Embedding, Deep learning, Word and Task research. His study focuses on the intersection of Word and fields such as Sentence with connections in the field of Theoretical computer science.

His research in Natural language processing intersects with topics in Representation and Substitution. His Automatic summarization course of study focuses on Artificial neural network and Task analysis, Visualization and Categorization. The concepts of his Machine learning study are interwoven with issues in Correctness, Structure, Training set and Knowledge graph.

Between 2019 and 2021, his most popular works were:

  • Pre-trained Models for Natural Language Processing: A Survey (59 citations)
  • Extractive Summarization as Text Matching (46 citations)
  • Heterogeneous Graph Neural Networks for Extractive Document Summarization. (29 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Natural language processing

Artificial intelligence, Natural language processing, Automatic summarization, Categorization and Machine learning are his primary areas of study. His study in Task, Machine translation, Joint, Dependency grammar and Text segmentation is carried out as part of his studies in Artificial intelligence. His work carried out in the field of Natural language processing brings together such families of science as Representation, Translation and Substitution.

His study brings together the fields of Artificial neural network and Automatic summarization. His study looks at the relationship between Categorization and fields such as Taxonomy, as well as how they intersect with chemical problems. His Machine learning research also works with subjects such as

  • Structure together with Base,
  • Language model which connect with Word and Theoretical computer science.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Recurrent Neural Network for Text Classification with Multi-Task Learning

Pengfei Liu;Xipeng Qiu;Xuanjing Huang.
arXiv: Computation and Language (2016)

542 Citations

How to Fine-Tune BERT for Text Classification?

Chi Sun;Xipeng Qiu;Yige Xu;Xuanjing Huang.
China National Conference on Chinese Computational Linguistics (2019)

413 Citations

Adversarial Multi-task Learning for Text Classification

Pengfei Liu;Xipeng Qiu;Xuanjing Huang.
meeting of the association for computational linguistics (2017)

391 Citations

Convolutional neural tensor network architecture for community-based question answering

Xipeng Qiu;Xuanjing Huang.
international conference on artificial intelligence (2015)

275 Citations

Long Short-Term Memory Neural Networks for Chinese Word Segmentation

Xinchi Chen;Xipeng Qiu;Chenxi Zhu;Pengfei Liu.
empirical methods in natural language processing (2015)

266 Citations

Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence

Chi Sun;Luyao Huang;Xipeng Qiu.
north american chapter of the association for computational linguistics (2019)

205 Citations

Pre-trained Models for Natural Language Processing: A Survey

XiPeng Qiu;TianXiang Sun;YiGe Xu;YunFan Shao.
Science China-technological Sciences (2020)

191 Citations

Multi-Timescale Long Short-Term Memory Neural Network for Modelling Sentences and Documents

Pengfei Liu;Xipeng Qiu;Xinchi Chen;Shiyu Wu.
empirical methods in natural language processing (2015)

132 Citations

Cached Long Short-Term Memory Neural Networks for Document-Level Sentiment Classification

Jiacheng Xu;Danlu Chen;Xipeng Qiu;Xuangjing Huang.
empirical methods in natural language processing (2016)

130 Citations

Gated Recursive Neural Network for Chinese Word Segmentation

Xinchi Chen;Xipeng Qiu;Chenxi Zhu;Xuanjing Huang.
international joint conference on natural language processing (2015)

124 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Xipeng Qiu

Yue Zhang

Yue Zhang

Westlake University

Publications: 35

Maosong Sun

Maosong Sun

Tsinghua University

Publications: 34

Hai Zhao

Hai Zhao

Shanghai Jiao Tong University

Publications: 34

Xuanjing Huang

Xuanjing Huang

Fudan University

Publications: 30

Min Zhang

Min Zhang

Tsinghua University

Publications: 26

Xueqi Cheng

Xueqi Cheng

Chinese Academy of Sciences

Publications: 26

Jie Zhou

Jie Zhou

Tsinghua University

Publications: 25

Jiafeng Guo

Jiafeng Guo

Chinese Academy of Sciences

Publications: 24

Minlie Huang

Minlie Huang

Tsinghua University

Publications: 20

Ting Liu

Ting Liu

Harbin Institute of Technology

Publications: 19

Guodong Zhou

Guodong Zhou

Soochow University

Publications: 19

Yonatan Belinkov

Yonatan Belinkov

Technion – Israel Institute of Technology

Publications: 19

Luo Si

Luo Si

Alibaba Group (China)

Publications: 18

Bing Liu

Bing Liu

Peking University

Publications: 17

Graham Neubig

Graham Neubig

Carnegie Mellon University

Publications: 16

W. Bruce Croft

W. Bruce Croft

University of Massachusetts Amherst

Publications: 16

Something went wrong. Please try again later.