World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
60
Citations
12697
World Ranking
3279
National Ranking
1588

Benjamin Van Durme 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 Benjamin Van Durme 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: 283 publications — 70th percentile

70% of scientists in this discipline score the same or lower.

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

Benjamin Van Durme 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 Benjamin Van Durme 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: 60 D-Index — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Overview

Benjamin Van Durme is affiliated with Johns Hopkins University in the United States. Their research primarily falls within the field of Computer Science, with a particular focus on Artificial Intelligence. The work spans multiple subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Political Science and International Relations, and Law.

Their research topics cover a range of areas in computational and applied linguistics, including:

  • Natural Language Processing Techniques
  • Topic Modeling
  • Multimodal Machine Learning Applications
  • Artificial Intelligence in Law
  • Text Readability and Simplification
  • Domain Adaptation and Few-Shot Learning
  • Software Engineering Research

Benjamin Van Durme has contributed to numerous publications, with prolific output in various prestigious venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Transactions of the Association for Computational Linguistics
  • Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Proceedings of the AAAI Conference on Artificial Intelligence

Selected recent papers authored or co-authored by Benjamin Van Durme are:

  • Constrained Language Models Yield Few-Shot Semantic Parsers, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine Translation, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Few-Shot Semantic Parsing with Language Models Trained on Code, 2022, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering, 2020, arXiv (Cornell University)
  • Pretrained Models for Multilingual Federated Learning, 2022, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Frequent collaborators in their research include Orion Weller, Daniel Khashabi, Dawn Lawrie, Patrick Xia, and Nathaniel Weir. These co-authors have contributed to multiple publications alongside Benjamin Van Durme, indicating ongoing academic partnerships.

Best Publications

  • PPDB: The Paraphrase Database

    Juri Ganitkevitch;Benjamin Van Durme;Chris Callison-Burch

  • Information Extraction over Structured Data: Question Answering with Freebase

    Xuchen Yao;Benjamin Van Durme

  • Hypothesis Only Baselines in Natural Language Inference

    Adam Poliak;Jason Naradowsky;Aparajita Haldar;Rachel Rudinger

  • Gender Bias in Coreference Resolution

    Rachel Rudinger;Jason Naradowsky;Brian Leonard;Benjamin Van Durme

  • What do you learn from context? Probing for sentence structure in contextualized word representations

    Ian Tenney;Patrick Xia;Berlin Chen;Alex Wang

  • PPDB 2.0: Better paraphrase ranking, fine-grained entailment relations, word embeddings, and style classification

    Ellie Pavlick;Pushpendre Rastogi;Juri Ganitkevitch;Benjamin Van Durme

  • Annotated Gigaword

    Courtney Napoles;Matthew Gormley;Benjamin Van Durme

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

    Sheng Zhang;Xiaodong Liu;Jingjing Liu;Jianfeng Gao

  • Answer Extraction as Sequence Tagging with Tree Edit Distance

    Xuchen Yao;Benjamin Van Durme;Chris Callison-Burch;Peter Clark

  • Open Domain Targeted Sentiment

    Margaret Mitchell;Jacqui Aguilar;Theresa Wilson;Benjamin Van Durme

  • Efficient spoken term discovery using randomized algorithms

    Aren Jansen;Benjamin Van Durme

  • Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation

    Adam Poliak;Aparajita Haldar;Rachel Rudinger;J. Edward Hu

  • What you seek is what you get: extraction of class attributes from query logs

    Marius Pasca;Benjamin Van Durme

  • Reporting bias and knowledge acquisition

    Jonathan Gordon;Benjamin Van Durme

  • Inferring User Political Preferences from Streaming Communications

    Svitlana Volkova;Glen Coppersmith;Benjamin Van Durme

  • Universal Decompositional Semantics on Universal Dependencies.

    Aaron Steven White;Dee Ann Reisinger;Keisuke Sakaguchi;Tim Vieira

  • Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation

    Unknown

  • Constrained Language Models Yield Few-Shot Semantic Parsers

    Richard Shin;Christopher H. Lin;Sam Thomson;Charles Chen

  • Weakly-Supervised Acquisition of Open-Domain Classes and Class Attributes from Web Documents and Query Logs

    Marius Paşca;Benjamin Van Durme

  • Ordinal Common-sense Inference

    Sheng Zhang;Rachel Rudinger;Kevin Duh;Benjamin Van Durme

  • Improved Lexically Constrained Decoding for Translation and Monolingual Rewriting

    J. Edward Hu;Huda Khayrallah;Ryan Culkin;Patrick Xia

  • Multi-Sentence Argument Linking.

    Seth Ebner;Patrick Xia;Ryan Culkin;Kyle Rawlins

  • Social Bias in Elicited Natural Language Inferences

    Rachel Rudinger;Chandler May;Benjamin Van Durme

Frequent Co-Authors

Kevin Duh
Kevin Duh Johns Hopkins University
Chris Callison-Burch
Chris Callison-Burch University of Pennsylvania
Ellie Pavlick
Ellie Pavlick Brown University
Mark Dredze
Mark Dredze Johns Hopkins University
Lenhart K. Schubert
Lenhart K. Schubert University of Rochester
Samuel R. Bowman
Samuel R. Bowman New York University
Yonatan Belinkov
Yonatan Belinkov Technion – Israel Institute of Technology
Ryan Cotterell
Ryan Cotterell ETH Zurich
Stuart M. Shieber
Stuart M. Shieber Harvard University
Margaret Mitchell
Margaret Mitchell Hugging Face

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