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Yoav Goldberg

Yoav Goldberg

D-Index & Metrics

Computer Science

D-Index
69
Citations
29643
World Ranking
1929
National Ranking
36

Overview

Yoav Goldberg is affiliated with Bar-Ilan University in Israel and specializes in computer science with a focus on artificial intelligence. Their work extends into several subfields including computer vision and pattern recognition, molecular biology, computational theory and mathematics, and information systems.

Their research concentrates on a diverse range of topics related to machine learning and natural language processing. Key topics include:

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

Yoav Goldberg has published extensively, with recent notable papers showcasing a range of interests within AI and computational linguistics:

  • Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks, 2024, arXiv (Cornell University)
  • Measuring and Improving Consistency in Pretrained Language Models, 2021, Transactions of the Association for Computational Linguistics
  • Universal Dependencies, 2025, Elsevier eBooks
  • oLMpics-On What Language Model Pre-training Captures, 2020, Transactions of the Association for Computational Linguistics
  • Amnesic Probing: Behavioral Explanation with Amnesic Counterfactuals, 2021, Transactions of the Association for Computational Linguistics

Their collaborations feature several frequent co-authors, highlighting ongoing research partnerships. Prominent collaborators include:

  • Shauli Ravfogel
  • Yanai Elazar
  • Reut Tsarfaty
  • Alon Jacovi
  • Hillel Taub-Tabib

Publications appear regularly in respected venues such as:

  • arXiv (Cornell University)
  • Transactions of the Association for Computational Linguistics
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Machine Learning
  • bioRxiv (Cold Spring Harbor Laboratory)

Best Publications

  • Neural Word Embedding as Implicit Matrix Factorization

    Omer Levy;Yoav Goldberg

  • Improving Distributional Similarity with Lessons Learned from Word Embeddings

    Omer Levy;Yoav Goldberg;Ido Dagan

  • word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding method.

    Yoav Goldberg;Omer Levy

  • Dependency-Based Word Embeddings

    Omer Levy;Yoav Goldberg

  • A primer on neural network models for natural language processing

    Yoav Goldberg

  • Universal Dependencies v1: A Multilingual Treebank Collection

    Joakim Nivre;Marie-Catherine de Marneffe;Filip Ginter;Yoav Goldberg

  • Neural Network Methods in Natural Language Processing

    Yoav Goldberg;Graeme Hirst

  • Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies

    Tal Linzen;Emmanuel Dupoux;Yoav Goldberg

  • Linguistic Regularities in Sparse and Explicit Word Representations

    Omer Levy;Yoav Goldberg

  • Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations

    Eliyahu Kiperwasser;Yoav Goldberg

  • Universal Dependency Annotation for Multilingual Parsing

    Ryan McDonald;Joakim Nivre;Yvonne Quirmbach-Brundage;Yoav Goldberg

  • BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models

    Elad Ben Zaken;Shauli Ravfogel;Yoav Goldberg

  • DyNet: The Dynamic Neural Network Toolkit

    Graham Neubig;Chris Dyer;Yoav Goldberg;Austin Matthews

  • Assessing BERT's Syntactic Abilities.

    Yoav Goldberg

  • Breaking NLI Systems with Sentences that Require Simple Lexical Inferences

    Max Glockner;Vered Shwartz;Yoav Goldberg

  • Deep multi-task learning with low level tasks supervised at lower layers

    Anders Søgaard;Yoav Goldberg

  • Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them

    Hila Gonen;Yoav Goldberg

  • Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks

    Yossi Adi;Einat Kermany;Yonatan Belinkov;Ofer Lavi

  • Multilingual Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Models and Auxiliary Loss

    Barbara Plank;Anders Søgaard;Yoav Goldberg

  • Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI

    Alon Jacovi;Ana Marasović;Tim Miller;Yoav Goldberg

  • Universal Dependencies 2.7

    Daniel Zeman;Joakim Nivre;Mitchell Abrams;Elia Ackermann

Frequent Co-Authors

Ido Dagan
Ido Dagan Bar-Ilan University
Joakim Nivre
Joakim Nivre Uppsala University
Anders Søgaard
Anders Søgaard University of Copenhagen
Eran Yahav
Eran Yahav Technion – Israel Institute of Technology
Omer Levy
Omer Levy Deep Mind
Jonathan Berant
Jonathan Berant Tel Aviv University
Noah A. Smith
Noah A. Smith University of Washington
Chris Dyer
Chris Dyer Google (United States)

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