World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
8764
World Ranking
5932
National Ranking
2676

Jason Baldridge publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Jason Baldridge sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 250 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 560 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 118 publications — 14th percentile

14% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Jason Baldridge D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Jason Baldridge sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 49 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Jason Baldridge is a researcher affiliated with Google in the United States, principally working within the field of computer science. Their research portfolio includes a significant focus on computer vision and pattern recognition, as well as artificial intelligence, geography, planning and development, aerospace engineering, and geology. Their contributions have positioned them prominently in areas related to machine learning and multimodal data understanding.

The scientist's recent publications reflect a strong emphasis on generative models, language processing, and integration of multimodal data. Notable papers include:

  • Scaling Autoregressive Models for Content-Rich Text-to-Image Generation (2022, arXiv (Cornell University))
  • Placing language in an integrated understanding system: Next steps toward human-level performance in neural language models (2020, Proceedings of the National Academy of Sciences)
  • Vector-quantized Image Modeling with Improved VQGAN (2021, arXiv (Cornell University))
  • Less is More: Generating Grounded Navigation Instructions from Landmarks (2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR))
  • Cross-Modal Contrastive Learning for Text-to-Image Generation (2021, arXiv (Cornell University))

Collaborations have been a notable part of their career, with frequent co-authors including:

  • Alexander Ku
  • Jing Yu Koh
  • Jordi Pont-Tuset
  • Su Wang
  • Yasumasa Onoe

Their work is predominantly published in well-known venues, with repeated contributions to:

  • arXiv (Cornell University)
  • Proceedings of the National Academy of Sciences
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Their research covers several interrelated topics, including:

  • Multimodal Machine Learning Applications
  • Advanced Image and Video Retrieval Techniques
  • Topic Modeling
  • Natural Language Processing Techniques
  • Geographic Information Systems Studies
  • Generative Adversarial Networks and Image Synthesis
  • Domain Adaptation and Few-Shot Learning

Jason Baldridge's interdisciplinary work spans from developing foundational techniques in computer vision and natural language processing to applied research in geographic information systems and aerospace domain challenges. Their body of work reflects a broad engagement with both theoretical and practical aspects of modern machine learning methodologies and their applications.

Best Publications

  • Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

    Unknown

  • Twitter Polarity Classification with Label Propagation over Lexical Links and the Follower Graph

    Michael Speriosu;Nikita Sudan;Sid Upadhyay;Jason Baldridge

  • Combinatory Categorial Grammar

    Mark Steedman;Jason Baldridge

  • Cross-Modal Contrastive Learning for Text-to-Image Generation

    Han Zhang;Jing Yu Koh;Jason Baldridge;Honglak Lee

  • Simple supervised document geolocation with geodesic grids

    Benjamin Wing;Jason Baldridge

  • PAWS: Paraphrase Adversaries from Word Scrambling

    Yuan Zhang;Jason Baldridge;Luheng He

  • PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification

    Yinfei Yang;Yuan Zhang;Chris Tar;Jason Baldridge

  • Supervised Text-based Geolocation Using Language Models on an Adaptive Grid

    Stephen Roller;Michael Speriosu;Sarat Rallapalli;Benjamin Wing

  • Mind the GAP: A Balanced Corpus of Gendered Ambiguous Pronouns

    Kellie Webster;Marta Recasens;Vera Axelrod;Jason Baldridge

  • Lexically specified derivational control in combinatory categorial grammar

    Jason Baldridge

  • Joint Determination of Anaphoricity and Coreference Resolution using Integer Programming

    Pascal Denis;Jason Baldridge

  • Room-Across-Room: Multilingual Vision-and-Language Navigation with Dense Spatiotemporal Grounding

    Alexander Ku;Peter Anderson;Roma Patel;Eugene Ie

  • Learning Dense Representations for Entity Retrieval

    Daniel Gillick;Sayali Kulkarni;Larry Lansing;Alessandro Presta

  • Multi-modal combinatory categorial grammar

    Jason Baldridge;Geert-Jan M. Kruijff

  • Specialized Models and Ranking for Coreference Resolution

    Pascal Denis;Jason Baldridge

  • Coupling CCG and Hybrid Logic Dependency Semantics

    Jason Baldridge;Geert-Jan Kruijff

  • Probabilistic Head-Driven Parsing for Discourse Structure

    Jason Baldridge;Alex Lascarides

  • Stay on the Path: Instruction Fidelity in Vision-and-Language Navigation

    Vihan Jain;Gabriel Magalhaes;Alexander Ku;Ashish Vaswani

  • Active Learning and the Total Cost of Annotation.

    Jason Baldridge;Miles Osborne

  • Hierarchical Discriminative Classification for Text-Based Geolocation

    Benjamin Wing;Jason Baldridge

  • Learning a Part-of-Speech Tagger from Two Hours of Annotation

    Dan Garrette;Jason Baldridge

Frequent Co-Authors

Katrin Erk
Katrin Erk The University of Texas at Austin
Honglak Lee
Honglak Lee University of Michigan–Ann Arbor
Miles Osborne
Miles Osborne Bloomberg LP
Noah A. Smith
Noah A. Smith University of Washington
Chris Dyer
Chris Dyer Google (United States)
Alex Lascarides
Alex Lascarides University of Edinburgh
Nicholas Asher
Nicholas Asher Toulouse Institute of Computer Science Research
Yoav Artzi
Yoav Artzi Cornell University
James L. McClelland
James L. McClelland Stanford University
Felix Hill
Felix Hill Google (United States)

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