World's Best Scientists 2026 revealed!
Jonathan Berant

Jonathan Berant

D-Index & Metrics

Computer Science

D-Index
55
Citations
12448
World Ranking
4301
National Ranking
66

Jonathan Berant 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 Jonathan Berant 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: 249 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: 559 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: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 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: 141 publications — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Jonathan Berant 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 Jonathan Berant sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 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: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Overview

Jonathan Berant is affiliated with Tel Aviv University in Israel and specializes primarily in Computer Science. Their research focuses extensively on Artificial Intelligence, with notable contributions in related subfields such as Computer Vision and Pattern Recognition, Information Systems, Molecular Biology, and Materials Chemistry.

The scientist's main topics of study include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Adversarial Robustness in Machine Learning
  • Speech and dialogue systems
  • Explainable Artificial Intelligence (XAI)

Jonathan Berant has published extensively in various academic venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Transactions of the Association for Computational Linguistics
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Their recent papers feature a range of topics related to natural language processing and machine learning. Notable recent publications include:

  • Learning To Retrieve Prompts for In-Context Learning (2022), published in Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies (2021), published in Transactions of the Association for Computational Linguistics
  • oLMpics-On What Language Model Pre-training Captures (2020), published in Transactions of the Association for Computational Linguistics
  • Break It Down: A Question Understanding Benchmark (2020), published in Transactions of the Association for Computational Linguistics
  • Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies (2021), published in arXiv (Cornell University)

Jonathan Berant collaborates frequently with several co-authors, including:

  • Mor Geva
  • Ori Yoran
  • Maor Ivgi
  • Ben Bogin
  • Tomer Wolfson

Best Publications

  • Semantic Parsing on Freebase from Question-Answer Pairs

    Jonathan Berant;Andrew Chou;Roy Frostig;Percy Liang

  • CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge

    Alon Talmor;Jonathan Herzig;Nicholas Lourie;Jonathan Berant

  • Semantic Parsing via Paraphrasing

    Jonathan Berant;Percy Liang

  • Learning To Retrieve Prompts for In-Context Learning

    Unknown

  • The Web as a Knowledge-Base for Answering Complex Questions

    Alon Talmor;Jonathan Berant

  • Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision

    Chen Liang;Chen Liang;Chen Liang;Jonathan Berant;Jonathan Berant;Jonathan Berant;Quoc V. Le;Quoc V. Le;Quoc V. Le;Kenneth D. Forbus

  • Building a Semantic Parser Overnight

    Yushi Wang;Jonathan Berant;Percy Liang

  • oLMpics-On What Language Model Pre-training Captures

    Alon Talmor;Yanai Elazar;Yoav Goldberg;Jonathan Berant

  • Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets

    Mor Geva;Yoav Goldberg;Jonathan Berant

  • Evaluating Models’ Local Decision Boundaries via Contrast Sets

    Matt Gardner;Yoav Artzi;Victoria Basmov;Jonathan Berant

  • Modeling Biological Processes for Reading Comprehension

    Jonathan Berant;Vivek Srikumar;Pei-Chun Chen;Abby Vander Linden

  • Learning Recurrent Span Representations for Extractive Question Answering

    Kenton Lee;Shimi Salant;Tom Kwiatkowski;Ankur Parikh

  • MultiQA: An Empirical Investigation of Generalization and Transfer in Reading Comprehension

    Alon Talmor;Jonathan Berant

  • Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies

    Mor Geva;Daniel Khashabi;Elad Segal;Tushar Khot

  • Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing.

    Ben Bogin;Jonathan Berant;Matt Gardner

  • Coarse-to-Fine Question Answering for Long Documents

    Eunsol Choi;Daniel Hewlett;Jakob Uszkoreit;Illia Polosukhin

  • Injecting Numerical Reasoning Skills into Language Models

    Mor Geva;Ankit Gupta;Jonathan Berant

  • Global Learning of Typed Entailment Rules

    Jonathan Berant;Ido Dagan;Jacob Goldberger

  • Text Segmentation as a Supervised Learning Task

    Omri Koshorek;Adir Cohen;Noam Mor;Michael Rotman

  • Making Retrieval-Augmented Language Models Robust to Irrelevant Context

    Unknown

  • Break It Down: A Question Understanding Benchmark

    Tomer Wolfson;Tomer Wolfson;Mor Geva;Mor Geva;Ankit Gupta;Matt Gardner

  • Evaluating Models' Local Decision Boundaries via Contrast Sets.

    Matt Gardner;Yoav Artzi;Victoria Basmova;Jonathan Berant

Frequent Co-Authors

Amir Globerson
Amir Globerson Tel Aviv University
Matt Gardner
Matt Gardner Allen Institute for Artificial Intelligence
Ido Dagan
Ido Dagan Bar-Ilan University
Quoc V. Le
Quoc V. Le Google (United States)
Gal Chechik
Gal Chechik Bar-Ilan University
Yoav Goldberg
Yoav Goldberg Bar-Ilan University
Jacob Goldberger
Jacob Goldberger Bar-Ilan University
Hannaneh Hajishirzi
Hannaneh Hajishirzi University of Washington
Sameer Singh
Sameer Singh University of California, Irvine
Peter Clark
Peter Clark Allen Institute for Artificial Intelligence

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