World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
71
Citations
57013
World Ranking
1719
National Ranking
873

Overview

Yiming Yang is affiliated with Carnegie Mellon University in the United States and has a research focus primarily within the field of Computer Science. Their work spans several specialized subfields, including Artificial Intelligence, Computer Vision and Pattern Recognition, Mechanical Engineering, Statistical and Nonlinear Physics, and Developmental and Educational Psychology.

Their research topics cover a diverse range of advanced techniques and applications. Key areas include Topic Modeling, Natural Language Processing Techniques, Advanced Graph Neural Networks, Multimodal Machine Learning Applications, Video Surveillance and Tracking Methods, Complex Network Analysis Techniques, and Speech Recognition and Synthesis.

Yiming Yang's recent scholarly contributions include several papers published in notable venues. These include:

  • "Xlnet: Generalized Autoregressive Pretraining for Language Understanding", 2025, arXiv (Cornell University)
  • "CAWET: Context-Aware Worst-Case Execution Time Estimation Using Transformers", 2023, arXiv (Cornell University)
  • "Rethinking Transformer-based Set Prediction for Object Detection", 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "JAKET: Joint Pre-training of Knowledge Graph and Language Understanding", 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing", 2020, arXiv (Cornell University)

Frequent coauthors of Yiming Yang include Donghan Yu, Aman Madaan, Ruohong Zhang, Zihang Dai, and Quoc V. Le. Collaboration with these researchers spans numerous projects and publications, indicating a network of joint research efforts within the academic community.

The venues where Yiming Yang most often publishes reflect their research interests and visibility in the academic domain. These include arXiv (Cornell University), Teaching and Teacher Education, the 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Proceedings of the AAAI Conference on Artificial Intelligence, and Multimedia Tools and Applications.

Best Publications

  • A Comparative Study on Feature Selection in Text Categorization

    Yiming Yang;Jan O. Pedersen

  • XLNet: Generalized Autoregressive Pretraining for Language Understanding

    Zhilin Yang;Zihang Dai;Yiming Yang;Jaime G. Carbonell

  • A re-examination of text categorization methods

    Yiming Yang;Xin Liu

  • Transformer-XL: Attentive Language Models beyond a Fixed-Length Context.

    Zihang Dai;Zhilin Yang;Yiming Yang;Jaime G. Carbonell

  • RCV1: A New Benchmark Collection for Text Categorization Research

    David D. Lewis;Yiming Yang;Tony G. Rose;Fan Li

  • An Evaluation of Statistical Approaches to Text Categorization

    Yiming Yang

  • DARTS: Differentiable Architecture Search

    Hanxiao Liu;Karen Simonyan;Yiming Yang

  • Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks

    Guokun Lai;Wei-Cheng Chang;Yiming Yang;Hanxiao Liu

  • Topic Detection and Tracking Pilot Study Final Report

    James Allan;Jaime Carbonell;George Doddington;Jonathan Yamron

  • The enron corpus: a new dataset for email classification research

    Bryan Klimt;Yiming Yang

  • A study of retrospective and on-line event detection

    Yiming Yang;Tom Pierce;Jaime Carbonell

  • RACE: Large-scale ReAding Comprehension Dataset From Examinations

    Guokun Lai;Qizhe Xie;Hanxiao Liu;Yiming Yang

  • Introducing the Enron Corpus.

    Bryan Klimt;Yiming Yang

  • An example-based mapping method for text categorization and retrieval

    Yiming Yang;Christopher G. Chute

  • MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices

    Zhiqing Sun;Hongkun Yu;Xiaodan Song;Renjie Liu

  • Expert network: effective and efficient learning from human decisions in text categorization and retrieval

    Yiming Yang

  • Deep Learning for Extreme Multi-label Text Classification

    Jingzhou Liu;Wei-Cheng Chang;Yuexin Wu;Yiming Yang

  • On the Sentence Embeddings from Pre-trained Language Models

    Bohan Li;Hao Zhou;Junxian He;Mingxuan Wang

  • Learning approaches for detecting and tracking news events

    Y. Yang;J.G. Carbonell;R.D. Brown;T. Pierce

  • MMD GAN: Towards Deeper Understanding of Moment Matching Network

    Chun-Liang Li;Wei-Cheng Chang;Yu Cheng;Yiming Yang

  • High-performing feature selection for text classification

    Monica Rogati;Yiming Yang

Frequent Co-Authors

Jaime G. Carbonell
Jaime G. Carbonell Carnegie Mellon University
Christopher G. Chute
Christopher G. Chute Johns Hopkins University
Graham Neubig
Graham Neubig Carnegie Mellon University
Barnabás Póczos
Barnabás Póczos Carnegie Mellon University
Ruslan Salakhutdinov
Ruslan Salakhutdinov Carnegie Mellon University
Eduard Hovy
Eduard Hovy Carnegie Mellon University
Inderjit S. Dhillon
Inderjit S. Dhillon Google (United States)
Quoc V. Le
Quoc V. Le Google (United States)
Alan W. Black
Alan W. Black Carnegie Mellon University

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