World's Best Scientists 2026 revealed!

Naoaki Okazaki 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 Naoaki Okazaki 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+

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

Naoaki Okazaki 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 Naoaki Okazaki 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+

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

Overview

Naoaki Okazaki is affiliated with the Tokyo Institute of Technology in Japan. Their research primarily lies within the field of Computer Science, with a focus on subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computational Theory and Mathematics, and General Health Professions.

The main topics addressed in Okazaki's work include:

  • Natural Language Processing Techniques
  • Topic Modeling
  • Multimodal Machine Learning Applications
  • Text Readability and Simplification
  • Advanced Text Analysis Techniques
  • Speech Recognition and Synthesis
  • Domain Adaptation and Few-Shot Learning

Okazaki has contributed extensively to academic literature with 196 publications in total. They have published significantly in venues such as:

  • arXiv (Cornell University)
  • Journal of Natural Language Processing
  • Journal of Information Processing
  • ACM Transactions on Asian and Low-Resource Language Information Processing
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Some of Okazaki's recent papers include:

  • OUTFOX: LLM-Generated Essay Detection Through In-Context Learning with Adversarially Generated Examples, 2024, Proceedings of the AAAI Conference on Artificial Intelligence
  • Gender Bias in Masked Language Models for Multiple Languages, 2022, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Named Entity Recognition and Relation Extraction Using Enhanced Table Filling by Contextualized Representations, 2022, Journal of Natural Language Processing
  • Transformer-based Lexically Constrained Headline Generation, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • It's Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information, 2020, arXiv (Cornell University)

Okazaki has collaborated frequently with several researchers, notably:

  • Masahiro Kaneko
  • Sho Takase
  • Tatsuya Hiraoka
  • Youmi Ma
  • Mengsay Loem

In addition to journal and conference publications, Okazaki has contributed to book literature, with a recorded publication in the field by Springer Science+Business Media titled New Frontiers in Artificial Intelligence in 2020.

Best Publications

  • Identifying Sections in Scientific Abstracts using Conditional Random Fields

    Kenji Hirohata;Naoaki Okazaki;Sophia Ananiadou;Mitsuru Ishizuka

  • The gene normalization task in BioCreative III

    Zhiyong Lu;Hung-Yu Kao;Chih-Hsuan Wei;Minlie Huang

  • Supporting Systematic Reviews Using Text Mining

    Sophia Ananiadou;Brian Rea;Naoaki Okazaki;Rob Procter

  • Neural Headline Generation on Abstract Meaning Representation

    Sho Takase;Jun Suzuki;Naoaki Okazaki;Tsutomu Hirao

  • Unsupervised Relation Extraction by Mining Wikipedia Texts Using Information from the Web

    Yulan Yan;Naoaki Okazaki;Yutaka Matsuo;Zhenglu Yang

  • A bottom-up approach to sentence ordering for multi-document summarization

    Danushka Bollegala;Naoaki Okazaki;Mitsuru Ishizuka

  • Building an abbreviation dictionary using a term recognition approach

    Naoaki Okazaki;Sophia Ananiadou

  • BioCreative III interactive task: an overview.

    Cecilia N Arighi;Phoebe M Roberts;Shashank Agarwal;Sanmitra Bhattacharya

  • Positional Encoding to Control Output Sequence Length

    Sho Takase;Naoaki Okazaki

  • Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs

    Emanuele Bugliarello;Ryan Cotterell;Ryan Cotterell;Naoaki Okazaki;Desmond Elliott

  • Simple and Efficient Algorithm for Approximate Dictionary Matching

    Naoaki Okazaki;Jun'ichi Tsujii

  • Building a high-quality sense inventory for improved abbreviation disambiguation

    Naoaki Okazaki;Sophia Ananiadou;Jun'ichi Tsujii

  • Improving chronological sentence ordering by precedence relation

    Naoaki Okazaki;Yutaka Matsuo;Mitsuru Ishizuka

  • Enhancing Machine Translation with Dependency-Aware Self-Attention

    Emanuele Bugliarello;Naoaki Okazaki

  • Named entity recognition with multiple segment representations

    Han-Cheol Cho;Naoaki Okazaki;Makoto Miwa;Jun'Ichi Tsujii

  • Dynamic entity representation with max-pooling improves machine reading

    Sosuke Kobayashi;Ran Tian;Naoaki Okazaki;Kentaro Inui

  • Improving Truthfulness of Headline Generation

    Kazuki Matsumaru;Sho Takase;Naoaki Okazaki

  • Kleio: a knowledge-enriched information retrieval system for biology

    Chikashi Nobata;Philip Cotter;Naoaki Okazaki;Brian Rea

  • A Term Recognition Approach to Acronym Recognition

    Naoaki Okazaki;Sophia Ananiadou

  • A Discriminative Candidate Generator for String Transformations

    Naoaki Okazaki;Yoshimasa Tsuruoka;Sophia Ananiadou;Jun'ichi Tsujii

Frequent Co-Authors

Jun'ichi Tsujii
Jun'ichi Tsujii University of Manchester
Mitsuru Ishizuka
Mitsuru Ishizuka University of Tokyo
Sophia Ananiadou
Sophia Ananiadou University of Manchester
Yutaka Matsuo
Yutaka Matsuo University of Tokyo
Danushka Bollegala
Danushka Bollegala University of Liverpool
Ryan Cotterell
Ryan Cotterell ETH Zurich
Yusuke Miyao
Yusuke Miyao University of Tokyo
Yoshimasa Tsuruoka
Yoshimasa Tsuruoka University of Tokyo
Hiroaki Kitano
Hiroaki Kitano Okinawa Institute of Science and Technology

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