World's Best Scientists 2026 revealed!
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Rising Stars
2025

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Rising Stars

D-Index
52
Citations
24568
World Ranking
262
National Ranking
43

Computer Science

D-Index
53
Citations
23998
World Ranking
4681
National Ranking
2173

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Sebastian Ruder is affiliated with Google in the United States and works primarily in the field of computer science. Their research focuses extensively on artificial intelligence and natural language processing, contributing substantially to the advancement of these disciplines.

The scientist has published 167 papers in computer science, with 139 of those specifically in artificial intelligence. They have also contributed to subfields such as computer vision and pattern recognition, electrical and electronic engineering, information systems, and general health professions.

The main topics covered in their work include:

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

Among their recent publications are:

  • "XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization," 2020, arXiv (Cornell University)
  • "MasakhaNER: Named Entity Recognition for African Languages," 2021, Transactions of the Association for Computational Linguistics
  • "Long Range Arena: A Benchmark for Efficient Transformers," 2020, arXiv (Cornell University)
  • "PaLM 2 Technical Report," 2023, arXiv (Cornell University)
  • "Charformer: Fast Character Transformers via Gradient-based Subword Tokenization," 2021, arXiv (Cornell University)

They often publish in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Transactions of the Association for Computational Linguistics
  • HAL (Le Centre pour la Communication Scientifique Directe)

Frequently collaborating with other researchers, their most common coauthors include:

  • Graham Neubig
  • David Ifeoluwa Adelani
  • Samuel Cahyawijaya
  • Shamsuddeen Hassan Muhammad
  • Xinyi Wang

Best Publications

  • An overview of gradient descent optimization algorithms

    Sebastian Ruder

  • Universal Language Model Fine-tuning for Text Classification

    Jeremy Howard;Sebastian Ruder

  • An Overview of Multi-Task Learning in Deep Neural Networks

    Sebastian Ruder

  • A Survey Of Cross-lingual Word Embedding Models

    Sebastian Ruder;Ivan Vulić;Anders Søgaard

  • On the Cross-lingual Transferability of Monolingual Representations

    Mikel Artetxe;Sebastian Ruder;Dani Yogatama

  • PaLM 2 Technical Report

    Unknown

  • Transfer Learning in Natural Language Processing.

    Sebastian Ruder;Matthew E. Peters;Swabha Swayamdipta;Thomas Wolf

  • XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalisation

    Junjie Hu;Sebastian Ruder;Aditya Siddhant;Graham Neubig

  • Fine-tuned Language Models for Text Classification.

    Jeremy Howard;Sebastian Ruder

  • MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer

    Jonas Pfeiffer;Ivan Vulić;Iryna Gurevych;Sebastian Ruder

  • To Tune or Not to Tune? Adapting Pretrained Representations to Diverse Tasks

    Matthew E. Peters;Sebastian Ruder;Noah A. Smith

  • AdapterHub: A Framework for Adapting Transformers

    Jonas Pfeiffer;Andreas Rücklé;Clifton Poth;Aishwarya Kamath

  • XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization

    Junjie Hu;Sebastian Ruder;Aditya Siddhant;Graham Neubig

  • A Hierarchical Model of Reviews for Aspect-based Sentiment Analysis

    Sebastian Ruder;Parsa Ghaffari;John G. Breslin

  • On the Limitations of Unsupervised Bilingual Dictionary Induction

    Anders Søgaard;Sebastian Ruder;Ivan Vulić

  • Latent Multi-Task Architecture Learning

    Sebastian Ruder;Joachim Bingel;Isabelle Augenstein;Anders Søgaard

  • Long Range Arena : A Benchmark for Efficient Transformers

    Yi Tay;Mostafa Dehghani;Samira Abnar;Yikang Shen

  • Neural transfer learning for natural language processing

    Sebastian Ruder

  • A Hierarchical Multi-Task Approach for Learning Embeddings from Semantic Tasks

    Victor Sanh;Thomas Wolf;Sebastian Ruder

  • MasakhaNER: Named Entity Recognition for African Languages

    David Ifeoluwa Adelani;Jade Z. Abbott;Graham Neubig;Daniel D'souza

  • Episodic Memory in Lifelong Language Learning

    Cyprien de Masson d'Autume;Sebastian Ruder;Lingpeng Kong;Dani Yogatama

  • Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks

    Rabeeh Karimi Mahabadi;Sebastian Ruder;Mostafa Dehghani;James Henderson

Frequent Co-Authors

Anders Søgaard
Anders Søgaard University of Copenhagen
Ivan Vulić
Ivan Vulić University of Cambridge
Dani Yogatama
Dani Yogatama University of Southern California
John G. Breslin
John G. Breslin University of Galway
Graham Neubig
Graham Neubig Carnegie Mellon University
Iryna Gurevych
Iryna Gurevych Technical University of Darmstadt
Ryan Cotterell
Ryan Cotterell ETH Zurich
Isabelle Augenstein
Isabelle Augenstein University of Copenhagen
Barbara Plank
Barbara Plank Ludwig-Maximilians-Universität München
Yi Tay
Yi Tay Google (United States)

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