World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
59
Citations
14079
World Ranking
3419
National Ranking
457

Overview

Hua Wu is affiliated with Baidu (China) in China and works primarily in the field of Computer Science, with a significant focus on Artificial Intelligence. Their research portfolio includes contributions to Computer Vision and Pattern Recognition, Molecular Biology, Computational Theory and Mathematics, and Materials Chemistry.

The scientist's work covers a range of topics including Topic Modeling, Natural Language Processing Techniques, Multimodal Machine Learning Applications, Computational Drug Discovery Methods, Speech and Dialogue Systems, Machine Learning in Materials Science, and Text and Document Classification Technologies.

Notable recent publications by Hua Wu include:

  • ERNIE 2.0: A Continual Pre-Training Framework for Language Understanding, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Geometry-enhanced molecular representation learning for property prediction, 2022, Nature Machine Intelligence
  • Unified Structure Generation for Universal Information Extraction, 2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Pre-Trained Language Models and Their Applications, 2022, Engineering
  • ERNIE-ViL: Knowledge Enhanced Vision-Language Representations through Scene Graphs, 2021, Proceedings of the AAAI Conference on Artificial Intelligence

Frequent co-authors collaborating with Hua Wu include:

  • Haifeng Wang
  • Xinyan Xiao
  • Hao Tian
  • Xiaomin Fang
  • Shuohuan Wang

Common venues where Hua Wu's research has been published are:

  • arXiv (Cornell University)
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Engineering

Best Publications

  • ERNIE: Enhanced Representation through Knowledge Integration

    Yu Sun;Shuohuan Wang;Yukun Li;Shikun Feng

  • 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

  • Minimum Risk Training for Neural Machine Translation

    Shiqi Shen;Yong Cheng;Zhongjun He;Wei He

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

    Yingqi Qu;Yuchen Ding;Jing Liu;Kai Liu

  • An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global Knowledge

    Yanchao Hao;Yuanzhe Zhang;Kang Liu;Shizhu He

  • Learning to Respond with Deep Neural Networks for Retrieval-Based Human-Computer Conversation System

    Rui Yan;Yiping Song;Hua Wu

  • Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network

    Xiangyang Zhou;Lu Li;Daxiang Dong;Yi Liu

  • Pre-Trained Language Models and Their Applications

    Unknown

  • 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

  • Multi-view Response Selection for Human-Computer Conversation

    Xiangyang Zhou;Daxiang Dong;Hua Wu;Shiqi Zhao

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

    Wei He;Kai Liu;Jing Liu;Yajuan Lyu

  • Semi-Supervised Learning for Neural Machine Translation

    Yong Cheng;Wei Xu;Zhongjun He;Wei He

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

    Mingbo Ma;Liang Huang;Hao Xiong;Renjie Zheng

  • Learning to Select Knowledge for Response Generation in Dialog Systems

    Rongzhong Lian;Min Xie;Fan Wang;Jinhua Peng

  • 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

  • Towards Conversational Recommendation over Multi-Type Dialogs

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

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

    Fei Yu;Jiji Tang;Weichong Yin;Yu Sun

  • Proactive Human-Machine Conversation with Explicit Conversation Goals

    Wenquan Wu;Zhen Guo;Xiangyang Zhou;Hua Wu

Frequent Co-Authors

Haifeng Wang
Haifeng Wang Baidu (China)
Wanxiang Che
Wanxiang Che Harbin Institute of Technology
Ming Zhou
Ming Zhou Langboat Technology
Wayne Xin Zhao
Wayne Xin Zhao Renmin University of China
Ting Liu
Ting Liu Harbin Institute of Technology
Maosong Sun
Maosong Sun Tsinghua University
Yang Liu
Yang Liu Tsinghua University
Chengqing Zong
Chengqing Zong Chinese Academy of Sciences
Liang Huang
Liang Huang Oregon State University
Sujian Li
Sujian Li Peking University

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