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D-Index & Metrics

Computer Science

D-Index
53
Citations
27862
World Ranking
4677
National Ranking
2169

Overview

Samuel R. Bowman is affiliated with New York University in the United States. Their research primarily focuses on computer science, with a specialization in artificial intelligence. They have contributed notably to several related subfields including information systems, computer science applications, and computer vision and pattern recognition.

Their publications encompass a wide range of topics within the broader scope of artificial intelligence. Main areas of focus include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Explainable Artificial Intelligence (XAI)
  • Speech and Dialogue Systems
  • Mobile Crowdsensing and Crowdsourcing
  • Multimodal Machine Learning Applications
  • Text Readability and Simplification

Samuel R. Bowman has published extensively in academic venues. Frequent publication platforms include:

  • arXiv (Cornell University)
  • Transactions of the Association for Computational Linguistics
  • Critical AI
  • Proceedings of the AAAI Conference on Artificial Intelligence

Recent papers authored or coauthored by Bowman illustrate their involvement in contemporary research discussions. Notable papers include:

  • "Eight Things to Know about Large Language Models", 2023, arXiv (Cornell University)
  • "Constitutional AI: Harmlessness from AI Feedback", 2022, arXiv (Cornell University)
  • "Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting", 2023, arXiv (Cornell University)
  • "Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work?", 2020, arXiv (Cornell University)
  • "Towards Understanding Sycophancy in Language Models", 2023, arXiv (Cornell University)

Bowman has frequently collaborated with other researchers, with consistent coauthors being:

  • Ethan Perez
  • Jason Phang
  • Jared Kaplan
  • Alicia Parrish
  • Haokun Liu

With a publication record of 144 works in computer science and 126 in artificial intelligence alone, Bowman's academic output reflects sustained activity in these fields. Their extensive work on topic modeling and natural language processing techniques positions them within key areas of current AI research and development.

Best Publications

  • GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

    Alex Wang;Amanpreet Singh;Julian Michael;Felix Hill

  • A large annotated corpus for learning natural language inference

    Samuel R. Bowman;Gabor Angeli;Christopher Potts;Christopher D. Manning

  • A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference

    Adina Williams;Nikita Nangia;Samuel R. Bowman

  • Generating Sentences from a Continuous Space

    Samuel R. Bowman;Luke Vilnis;Oriol Vinyals;Andrew M. Dai

  • SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems

    Alex Wang;Yada Pruksachatkun;Nikita Nangia;Amanpreet Singh

  • Annotation Artifacts in Natural Language Inference Data

    Suchin Gururangan;Swabha Swayamdipta;Omer Levy;Roy Schwartz;Roy Schwartz

  • XNLI: Evaluating Cross-lingual Sentence Representations

    Alexis Conneau;Ruty Rinott;Guillaume Lample;Adina Williams

  • Neural Network Acceptability Judgments

    Alex Warstadt;Amanpreet Singh;Samuel R. Bowman

  • Universal Dependencies 2.2

    Joakim Nivre;Mitchell Abrams;Željko Agić;Lars Ahrenberg

  • Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks

    Jason Phang;Thibault Févry;Samuel R. Bowman

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

    Ian Tenney;Patrick Xia;Berlin Chen;Alex Wang

  • On Measuring Social Biases in Sentence Encoders

    Chandler May;Alex Wang;Shikha Bordia;Samuel R. Bowman

  • A Fast Unified Model for Parsing and Sentence Understanding

    Samuel R. Bowman;Jon Gauthier;Abhinav Rastogi;Raghav Gupta

  • CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models

    Nikita Nangia;Clara Vania;Rasika Bhalerao;Samuel R. Bowman

  • BLiMP: The Benchmark of Linguistic Minimal Pairs for English

    Alex Warstadt;Alicia Parrish;Haokun Liu;Anhad Mohananey

  • A Gold Standard Dependency Corpus for English

    Natalia Silveira;Timothy Dozat;Marie-Catherine de Marneffe;Samuel Bowman

  • Universal Dependencies 2.1

    Joakim Nivre;Željko Agić;Lars Ahrenberg;Lene Antonsen

  • XNLI: Evaluating Cross-lingual Sentence Representations

    Alexis Conneau;Guillaume Lample;Ruty Rinott;Adina Williams

  • Identifying and reducing gender bias in word-level language models

    Shikha Bordia;Samuel R. Bowman

  • Universal Dependencies 2.0

    Joakim Nivre;Željko Agić;Lars Ahrenberg;Maria Jesus Aranzabe

  • Universal Dependencies 2.7

    Daniel Zeman;Joakim Nivre;Mitchell Abrams;Elia Ackermann

Frequent Co-Authors

Christopher D. Manning
Christopher D. Manning Stanford University
Marie-Catherine de Marneffe
Marie-Catherine de Marneffe The Ohio State University
Jan Hajič
Jan Hajič Charles University
Sampo Pyysalo
Sampo Pyysalo University of Turku
Barbara Plank
Barbara Plank Ludwig-Maximilians-Universität München
Filip Ginter
Filip Ginter University of Turku
Slav Petrov
Slav Petrov Google (United States)
Joakim Nivre
Joakim Nivre Uppsala University

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