World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
32
Citations
9066
World Ranking
12878
National Ranking
5195

Overview

Yoav Artzi is affiliated with Cornell University in the United States and has made contributions primarily in the field of computer science. Their research spans multiple subfields including artificial intelligence, computer vision and pattern recognition, social psychology, geography, planning and development, and experimental and cognitive psychology.

The scientist's main research topics cover a range of computational and linguistic areas such as:

  • Topic Modeling
  • Multimodal Machine Learning Applications
  • Natural Language Processing Techniques
  • Speech and dialogue systems
  • Speech Recognition and Synthesis
  • Domain Adaptation and Few-Shot Learning
  • Advanced Image and Video Retrieval Techniques

Research outputs include numerous publications, with a significant number appearing on arXiv through Cornell University, alongside contributions to other venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Computer Speech & Language
  • Transactions of the Association for Computational Linguistics

Recent notable papers by Yoav Artzi include:

  • "Spoken language interaction with robots: Recommendations for future research" (2021, Computer Speech & Language)
  • "Revisiting Few-sample BERT Fine-tuning" (2020, arXiv (Cornell University))
  • "Evaluating Models' Local Decision Boundaries via Contrast Sets" (2020, arXiv (Cornell University))
  • "A Persistent Spatial Semantic Representation for High-level Natural Language Instruction Execution" (2021, arXiv (Cornell University))
  • "Performance-Efficiency Trade-Offs in Unsupervised Pre-Training for Speech Recognition" (2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP))

Frequent collaborators of the scientist include Kilian Q. Weinberger, Alane Suhr, Noriyuki Kojima, Kianté Brantley, and Valts Blukis.

Best Publications

  • BERTScore: Evaluating Text Generation with BERT

    Tianyi Zhang;Varsha Kishore;Felix Wu;Kilian Q. Weinberger

  • BERTScore: Evaluating Text Generation with BERT

    Tianyi Zhang;Varsha Kishore;Felix Wu;Kilian Q. Weinberger

  • Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies

    Max Grusky;Mor Naaman;Yoav Artzi

  • Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions

    Yoav Artzi;Luke Zettlemoyer

  • A Corpus for Reasoning about Natural Language Grounded in Photographs

    Alane Suhr;Stephanie Zhou;Ally Zhang;Iris Zhang

  • Learning to Automatically Solve Algebra Word Problems

    Nate Kushman;Yoav Artzi;Luke Zettlemoyer;Regina Barzilay

  • Scaling Semantic Parsers with On-the-Fly Ontology Matching

    Tom Kwiatkowski;Eunsol Choi;Yoav Artzi;Luke Zettlemoyer

  • Evaluating Models’ Local Decision Boundaries via Contrast Sets

    Matt Gardner;Yoav Artzi;Victoria Basmov;Jonathan Berant

  • TOUCHDOWN: Natural Language Navigation and Spatial Reasoning in Visual Street Environments

    Howard Chen;Alane Suhr;Dipendra Misra;Noah Snavely

  • Simple Recurrent Units for Highly Parallelizable Recurrence.

    Tao Lei;Yu Zhang;Sida I. Wang;Hui Dai

  • A Corpus of Natural Language for Visual Reasoning.

    Alane Suhr;Mike Lewis;James Yeh;Yoav Artzi

  • Revisiting Few-sample BERT Fine-tuning

    Tianyi Zhang;Felix Wu;Arzoo Katiyar;Kilian Q Weinberger

  • Mapping Instructions and Visual Observations to Actions with Reinforcement Learning.

    Dipendra Kumar Misra;John Langford;Yoav Artzi

  • Broad-coverage CCG Semantic Parsing with AMR

    Yoav Artzi;Kenton Lee;Luke Zettlemoyer

  • Training RNNs as Fast as CNNs

    Tao Lei;Yu Zhang;Yoav Artzi

  • Mapping Instructions to Actions in 3D Environments with Visual Goal Prediction

    Dipendra Kumar Misra;Andrew Bennett;Valts Blukis;Eyvind Niklasson

  • Bootstrapping Semantic Parsers from Conversations

    Yoav Artzi;Luke Zettlemoyer

  • Predicting Responses to Microblog Posts

    Yoav Artzi;Patrick Pantel;Michael Gamon

  • CHALET: Cornell House Agent Learning Environment.

    Claudia Yan;Dipendra Kumar Misra;Andrew Bennett;Aaron Walsman

  • Context-dependent Semantic Parsing for Time Expressions

    Kenton Lee;Yoav Artzi;Jesse Dodge;Luke Zettlemoyer

  • Evaluating Models' Local Decision Boundaries via Contrast Sets.

    Matt Gardner;Yoav Artzi;Victoria Basmova;Jonathan Berant

  • Spoken language interaction with robots: Recommendations for future research

    Matthew Marge;Carol Y. Espy-Wilson;Nigel G. Ward;Abeer Alwan

  • Learning Distributions over Logical Forms for Referring Expression Generation

    Nicholas FitzGerald;Yoav Artzi;Luke Zettlemoyer

  • Evaluating NLP Models via Contrast Sets

    Matt Gardner;Yoav Artzi;Victoria Basmova;Jonathan Berant

  • Event Detection and Factuality Assessment with Non-Expert Supervision

    Kenton Lee;Yoav Artzi;Yejin Choi;Luke Zettlemoyer

Frequent Co-Authors

Luke Zettlemoyer
Luke Zettlemoyer University of Washington
Kilian Q. Weinberger
Kilian Q. Weinberger Cornell University
Yejin Choi
Yejin Choi Stanford University
Dieter Fox
Dieter Fox University of Washington
Noah Snavely
Noah Snavely Cornell University
Mor Naaman
Mor Naaman Cornell University
Kenton Lee
Kenton Lee Google (United States)
Jonathan Berant
Jonathan Berant Tel Aviv University
Noah A. Smith
Noah A. Smith University of Washington
Sameer Singh
Sameer Singh University of California, Irvine

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