World's Best Scientists 2026 revealed!
Jingjing Liu

Jingjing Liu

D-Index & Metrics

Computer Science

D-Index
53
Citations
12792
World Ranking
4772
National Ranking
2220

Overview

Jingjing Liu is affiliated with MIT in the United States and has a significant body of research primarily in the field of Computer Science. Their work spans multiple subfields, including Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Media Technology, and Computational Mechanics.

The main topics explored in their research include:

  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Topic Modeling
  • Advanced Image and Video Retrieval Techniques
  • Image Enhancement Techniques
  • Natural Language Processing Techniques

Jingjing Liu's recent papers reflect a focus on vision and language representation learning, domain adaptation, and image detection techniques. Notable papers include:

  • "Large-Scale Adversarial Training for Vision-and-Language Representation Learning" (2020), published in arXiv (Cornell University)
  • "TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation" (2023), presented at the 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • "Insulator Faults Detection in Aerial Images from High-Voltage Transmission Lines Based on Deep Learning Model" (2021), published in Applied Sciences
  • "Improved YOLOv3 Network for Insulator Detection in Aerial Images with Diverse Background Interference" (2021), published in Electronics
  • "Target Detection of Forward-Looking Sonar Image Based on Improved YOLOv5" (2022), published in IEEE Access

Frequent coauthors in Jingjing Liu's collaborations include:

  • Zhe Gan
  • Linjie Li
  • Shuohang Wang
  • Yen-Chun Chen
  • Yu Cheng

Jingjing Liu has published extensively in several key venues, with numerous contributions to:

  • arXiv (Cornell University)
  • IEEE Access
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Energies
  • Neurocomputing

Their work is predominantly situated within advanced machine learning applications, integrating techniques in both computer vision and language modeling, underscoring an interdisciplinary approach across imaging and artificial intelligence domains.

Best Publications

  • UNITER: UNiversal Image-TExt Representation Learning

    Yen-Chun Chen;Linjie Li;Licheng Yu;Ahmed El Kholy

  • DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation

    Yizhe Zhang;Siqi Sun;Michel Galley;Yen-Chun Chen

  • Patient Knowledge Distillation for BERT Model Compression

    Siqi Sun;Yu Cheng;Zhe Gan;Jingjing Liu

  • Less is More: CLIPBERT for Video-and-Language Learning via Sparse Sampling

    Jie Lei;Linjie Li;Luowei Zhou;Zhe Gan

  • Low-Quality Product Review Detection in Opinion Summarization

    Jingjing Liu;Yunbo Cao;Chin-Yew Lin;Yalou Huang

  • Multispectral Deep Neural Networks for Pedestrian Detection

    Jingjing Liu;Shaoting Zhang;Shu Wang;Dimitris N. Metaxas

  • HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training

    Linjie Li;Yen-Chun Chen;Yu Cheng;Zhe Gan

  • Relation-Aware Graph Attention Network for Visual Question Answering

    Linjie Li;Zhe Gan;Yu Cheng;Jingjing Liu

  • FreeLB: Enhanced Adversarial Training for Natural Language Understanding

    Chen Zhu;Yu Cheng;Zhe Gan;Siqi Sun

  • UNITER: Learning UNiversal Image-TExt Representations

    Yen-Chun Chen;Linjie Li;Licheng Yu;Ahmed El Kholy

  • Large-Scale Adversarial Training for Vision-and-Language Representation Learning

    Zhe Gan;Yen-Chun Chen;Linjie Li;Chen Zhu

  • ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension.

    Sheng Zhang;Xiaodong Liu;Jingjing Liu;Jianfeng Gao

  • Discourse-Aware Neural Extractive Text Summarization

    Jiacheng Xu;Zhe Gan;Yu Cheng;Jingjing Liu

  • StoryGAN: A Sequential Conditional GAN for Story Visualization

    Yitong Li;Zhe Gan;Yelong Shen;Jingjing Liu

  • Deep Dyna-Q: Integrating Planning for Task-Completion Dialogue Policy Learning

    Baolin Peng;Xiujun Li;Jianfeng Gao;Jingjing Liu

  • Video search re-ranking via multi-graph propagation

    Jingjing Liu;Wei Lai;Xian-Sheng Hua;Yalou Huang

  • Hierarchical Graph Network for Multi-hop Question Answering

    Yuwei Fang;Siqi Sun;Zhe Gan;Rohit Pillai

  • TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation

    Unknown

  • Tactical Rewind: Self-Correction via Backtracking in Vision-And-Language Navigation

    Liyiming Ke;Xiujun Li;Yonatan Bisk;Ari Holtzman

  • Review Sentiment Scoring via a Parse-and-Paraphrase Paradigm

    Jingjing Liu;Stephanie Seneff

  • Integrating planning for task-completion dialogue policy learning.

    Baolin Peng;Xiujun Li;Jianfeng Gao;Jingjing Liu

Frequent Co-Authors

Zhe Gan
Zhe Gan Microsoft (United States)
Yu Cheng
Yu Cheng Microsoft (United States)
Jianfeng Gao
Jianfeng Gao Microsoft (United States)
Dimitris N. Metaxas
Dimitris N. Metaxas Rutgers, The State University of New Jersey
Lawrence Carin
Lawrence Carin Duke University
Zhangyang Wang
Zhangyang Wang The University of Texas at Austin
Shaoting Zhang
Shaoting Zhang University of Electronic Science and Technology of China
Tom Goldstein
Tom Goldstein University of Maryland, College Park
Jing Jiang
Jing Jiang Singapore Management University

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