2026 Jaime G. Carbonell: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	National Ranking	Publications	Citations
Computer Science	87	702	369	489	47147

Discipline name

D-Index

World Ranking

National Ranking

Publications

Citations

Computer Science

702

369

489

47147

Overview

Jaime G. Carbonell was affiliated with Carnegie Mellon University in the United States. Their research primarily focused on computer science, with a concentration on artificial intelligence. Other areas of their work included information systems, sociology and political science, developmental and educational psychology, and computer vision and pattern recognition.

Their investigations covered several research topics, such as:

Topic Modeling
Natural Language Processing Techniques
Speech Recognition and Synthesis
Hate Speech and Cyberbullying Detection
Multimodal Machine Learning Applications
Domain Adaptation and Few-Shot Learning
Information Retrieval and Search Behavior

Carbonell contributed to various publications, notably in these venues:

arXiv (Cornell University)
Proceedings of the International AAAI Conference on Web and Social Media
Proceedings of the AAAI Conference on Artificial Intelligence
Fordham University Press eBooks
TIB Data Manager

Among the recent papers associated with them were:

"Xlnet: Generalized Autoregressive Pretraining for Language Understanding," published in 2025 in arXiv (Cornell University)
"CAWET: Context-Aware Worst-Case Execution Time Estimation Using Transformers," published in 2023 in arXiv (Cornell University)
"Document Representation and Query Expansion Models for Blog Recommendation," published in 2021 in Proceedings of the International AAAI Conference on Web and Social Media
"Domain adaptation with invariant representation learning: What transformations to learn?," published in 2025 in TIB Data Manager
"Voice for the Voiceless: Active Sampling to Detect Comments Supporting the Rohingyas," published in 2020 in Proceedings of the AAAI Conference on Artificial Intelligence

Collaboration was part of their work, with frequent coauthors including Shriphani Palakodety, Ashiqur R. KhudaBukhsh, Zihang Dai, Zhilin Yang, and Yiming Yang. These collaborations reflected multidisciplinary approaches within the fields of study.

Best Publications

XLNet: Generalized Autoregressive Pretraining for Language Understanding

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

6940
Citations
Transformer-XL: Attentive Language Models beyond a Fixed-Length Context.

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

3595
Citations
Machine Learning: An Artificial Intelligence Approach

R. S. Michalski;J. G. Carbonell;T. M. Mitchell

2885
Citations
The Use of MMR and Diversity-Based Reranking for Reodering Documents and Producing Summaries

Jaime G. Carbonell;Jade Goldstein

2431
Citations
Topic Detection and Tracking Pilot Study Final Report

James Allan;Jaime Carbonell;George Doddington;Jonathan Yamron

1522
Citations
A study of retrospective and on-line event detection

Yiming Yang;Tom Pierce;Jaime Carbonell

1080
Citations
Derivational analogy: a theory of reconstructive problem solving and expertise acquisition

Jaime G. Carbonell

946
Citations
The Use of MMR, Diversity-Based Reranking for Reordering Documents and Producing Summaries

Unknown

911
Citations
Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization

Liang Xiong;Xi Chen;Tzu-Kuo Huang;Jeff G. Schneider

802
Citations
Summarizing text documents: sentence selection and evaluation metrics

Jade Goldstein;Mark Kantrowitz;Vibhu Mittal;Jaime Carbonell

704
Citations
Integrating planning and learning: the PRODIGY architecture

Manuela M. Veloso;Jaime G. Carbonell;M. Alicia Pérez;Daniel Borrajo

597
Citations
Learning by Analogy: Formulating and Generalizing Plans from Past Experience

Jaime G. Carbonell

592
Citations
An Overview of Machine Learning

Jaime G. Carbonell;Ryszard S. Michalski;Tom M. Mitchell

557
Citations
Multi-document summarization by sentence extraction

Jade Goldstein;Vibhu Mittal;Jaime Carbonell;Mark Kantrowitz

556
Citations
Learning approaches for detecting and tracking news events

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

544
Citations
User Models in Dialog Systems

S. Carberry;J. G. Carbonell;D. N. Chin;R. Cohen

437
Citations
Characterizing and Avoiding Negative Transfer

Zirui Wang;Zihang Dai;Barnabas Poczos;Jaime Carbonell

435
Citations
Explanation-based learning: a problem solving perspective

S. Minton;J. G. Carbonell;C. A. Knoblock;D. R. Kuokka

420
Citations
Integrated authoring and translation system

Peggy M Anderson;Kathryn L Baker;Michael M Bauer;Nicholas D Brownlow

392
Citations
Learning generative models for protein fold families.

Sivaraman Balakrishnan;Hetunandan Kamisetty;Jaime G. Carbonell;Su In Lee

388
Citations
Explanation-based learning: a problem solving perspective

Steven Minton;Jaime G. Carbonell;Craig A. Knoblock;Daniel R. Kuokka

315
Citations

Frequent Co-Authors

Yiming Yang Carnegie Mellon University

Judith Klein-Seetharaman Arizona State University

Lori Levin Carnegie Mellon University

Teruko Mitamura Carnegie Mellon University

Alon Lavie Carnegie Mellon University

Graham Neubig Carnegie Mellon University

Xi Chen Columbia University

Eric Nyberg Carnegie Mellon University

Stephan Vogel University of Graz

Jingrui He University of Illinois at Urbana-Champaign

External Links

Wikipedia of Jaime G. Carbonell Personal website of Jaime G. Carbonell Google Scholar page

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