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Haifeng Wang

Haifeng Wang

D-Index & Metrics

Computer Science

D-Index
58
Citations
12796
World Ranking
3645
National Ranking
486

Overview

Haifeng Wang is affiliated with Baidu in China and has a significant research footprint in computer science. Their main field of study is Computer Science, with a particular focus on Artificial Intelligence, which accounts for the majority of their publications. They have also contributed to research in related subfields such as Computer Vision and Pattern Recognition, Information Systems, Molecular Biology, and Materials Chemistry.

The scientist has explored several key research topics, including:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Speech and dialogue systems
  • Computational Drug Discovery Methods
  • Recommender Systems and Techniques
  • Advanced Text Analysis Techniques

Haifeng Wang has published papers in multiple well-known venues, with a strong presence on arXiv, which hosts the largest number of their works. Other frequent publication venues include the Proceedings of the AAAI Conference on Artificial Intelligence, the Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, the Proceedings of the 31st ACM International Conference on Information & Knowledge Management, and the journal Engineering.

Among their recent papers are:

  • "ERNIE 2.0: A Continual Pre-Training Framework for Language Understanding" (2020), published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • "Geometry-enhanced molecular representation learning for property prediction" (2022), published in Nature Machine Intelligence
  • "Pre-Trained Language Models and Their Applications" (2022), published in Engineering
  • "ERNIE-ViL: Knowledge Enhanced Vision-Language Representations through Scene Graphs" (2021), published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • "ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation" (2021), published on arXiv (Cornell University)

The scientist has collaborated frequently with a number of researchers, including Hua Wu, Jizhou Huang, Zheng-Yu Niu, and Hao Tian. Hua Wu is noted both as the most frequent coauthor as well as appearing multiple times in coauthor listings, indicating a significant research partnership.

Best Publications

  • Search engine with natural language-based robust parsing for user query and relevance feedback learning

    Hai-Feng Wang;Kai-Fu Lee;Qiang Yang

  • ERNIE 2.0: A Continual Pre-training Framework for Language Understanding

    Yu Sun;Shuohuan Wang;Yukun Li;Shikun Feng

  • Multi-Task Learning for Multiple Language Translation

    Daxiang Dong;Hua Wu;Wei He;Dianhai Yu

  • RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering

    Yingqi Qu;Yuchen Ding;Jing Liu;Kai Liu

  • Pre-Trained Language Models and Their Applications

    Unknown

  • Learning Semantic Hierarchies via Word Embeddings

    Ruiji Fu;Jiang Guo;Bing Qin;Wanxiang Che

  • Pivot Language Approach for Phrase-Based Statistical Machine Translation

    Hua Wu;Haifeng Wang

  • SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis

    Hao Tian;Can Gao;Xinyan Xiao;Hao Liu

  • PLATO: Pre-trained Dialogue Generation Model with Discrete Latent Variable

    Siqi Bao;Huang He;Fan Wang;Hua Wu

  • UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning

    Wei Li;Can Gao;Guocheng Niu;Xinyan Xiao

  • DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications

    Wei He;Kai Liu;Jing Liu;Yajuan Lyu

  • STACL: Simultaneous Translation with Implicit Anticipation and Controllable Latency using Prefix-to-Prefix Framework

    Mingbo Ma;Liang Huang;Hao Xiong;Renjie Zheng

  • ERNIE-ViL: Knowledge Enhanced Vision-Language Representations through Scene Graphs.

    Fei Yu;Jiji Tang;Weichong Yin;Yu Sun

  • ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation

    Yu Sun;Shuohuan Wang;Shikun Feng;Siyu Ding

  • Cross-lingual Dependency Parsing Based on Distributed Representations

    Jiang Guo;Wanxiang Che;David Yarowsky;Haifeng Wang

  • Proactive Human-Machine Conversation with Explicit Conversation Goal

    Wenquan Wu;Zhen Guo;Xiangyang Zhou;Hua Wu

  • Towards Conversational Recommendation over Multi-Type Dialogs

    Zeming Liu;Haifeng Wang;Zheng-Yu Niu;Hua Wu

  • HUMAN-COMPUTER INTERACTIVE METHOD AND APPARATUS BASED ON ARTIFICIAL INTELLIGENCE AND TERMINAL DEVICE

    Li Jialin;Jing Kun;Ge Xingfei;Wu Hua

  • Progress in Machine Translation

    Haifeng Wang;Hua Wu;Zhongjun He;Liang Huang

  • ConSTGAT: Contextual Spatial-Temporal Graph Attention Network for Travel Time Estimation at Baidu Maps

    Xiaomin Fang;Jizhou Huang;Fan Wang;Lingke Zeng

  • Revisiting Embedding Features for Simple Semi-supervised Learning

    Jiang Guo;Wanxiang Che;Haifeng Wang;Ting Liu

  • End-to-End Speech Translation with Knowledge Distillation.

    Yuchen Liu;Hao Xiong;Jiajun Zhang;Zhongjun He

  • ERNIE-ViL: Knowledge Enhanced Vision-Language Representations Through Scene Graph

    Fei Yu;Jiji Tang;Weichong Yin;Yu Sun

Frequent Co-Authors

Hua Wu
Hua Wu Baidu (China)
Ting Liu
Ting Liu Harbin Institute of Technology
Wanxiang Che
Wanxiang Che Harbin Institute of Technology
Chengqing Zong
Chengqing Zong Chinese Academy of Sciences
Kai-Fu Lee
Kai-Fu Lee Sinovation Ventures
Liang Huang
Liang Huang Oregon State University
Josef van Genabith
Josef van Genabith Saarland University
Ke Sun
Ke Sun Henry Patent Law Firm
Jianfeng Gao
Jianfeng Gao Microsoft (United States)
David Yarowsky
David Yarowsky Johns Hopkins University

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