Goldberg, Yoav

Neural Network Methods for Natural Language Processing

Goldberg, Y. (2017) · Synthesis Lectures on Human Language Technologies

Natural Language Processing TechniquesTopic Modeling

Cited by 821

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

Ben Zaken, E., Goldberg, Y., & Ravfogel, S. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 765

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

Jacovi, A., Marasović, A., Miller, T., & Goldberg, Y. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 545

Towards Faithfully Interpretable NLP Systems: How Should We Define and Evaluate Faithfulness?

Jacovi, A., & Goldberg, Y. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 503

Lipstick on a pig: Debiasing methods cover up systematic gender biases in word embeddings but do not remove them

Gonen, H., & Goldberg, Y. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)

Ethics and Social Impacts of AIGender Studies in Language

Cited by 454

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

Søgaard, A., & Goldberg, Y. (2016) · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

Natural Language Processing TechniquesDomain Adaptation and Few-Shot Learning

Cited by 445

Assessing BERT's Syntactic Abilities

Goldberg, Y. (2019) · arXiv

Natural Language Processing TechniquesSyntax, Semantics, Linguistic Variation

Cited by 385

Breaking NLI Systems with Sentences that Require Simple Lexical Inferences

Glockner, M., Shwartz, V., & Goldberg, Y. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 319

Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection

Ravfogel, S., Elazar, Y., Gonen, H., Twiton, M., & Goldberg, Y. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 287

Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets

Geva, M., Goldberg, Y., & Berant, J. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Natural Language Processing TechniquesTopic Modeling

Cited by 284

On the Practical Computational Power of Finite Precision RNNs for Language Recognition

Weiss, G., Goldberg, Y., & Yahav, E. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

semigroups and automata theoryNeural Networks and Applications

Cited by 226

Measuring and improving consistency in pretrained language models

Elazar, Y., Kassner, N., Ravfogel, S., Ravichander, A., Hovy, E., Schütze, H., & Goldberg, Y. (2021) · Transactions of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 220

Unsupervised Domain Clusters in Pretrained Language Models

Aharoni, R., & Goldberg, Y. (2020) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 187

Unsupervised Domain Clusters in Pretrained Language Models

Aharoni, R., & Goldberg, Y. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 181

Amnesic Probing: Behavioral Explanation with Amnesic Counterfactuals

Elazar, Y., Ravfogel, S., Jacovi, A., & Goldberg, Y. (2021) · Transactions of the Association for Computational Linguistics

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 126

Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Space

Geva, M., Caciularu, A., Wang, K. R., & Goldberg, Y. (2022) · arXiv

Topic ModelingExplainable Artificial Intelligence (XAI)

Cited by 123

Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models

Levy, M., Jacoby, A., & Goldberg, Y. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 119

Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models

Levy, M., Jacoby, A., & Goldberg, Y. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 119

Contrastive Explanations for Model Interpretability

Jacovi, A., Swayamdipta, S., Ravfogel, S., Elazar, Y., Choi, Y., & Goldberg, Y. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 83

Including Signed Languages in Natural Language Processing

Yin, K., Moryossef, A., Hochgesang, J., Goldberg, Y., & Alikhani, M. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Natural Language Processing TechniquesHearing Impairment and Communication

Cited by 79

Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation

Gamrian, S., & Goldberg, Y. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 70

Simple, Interpretable and Stable Method for Detecting Words with Usage Change across Corpora

Gonen, H., Jawahar, G., Seddah, D., & Goldberg, Y. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Digital Humanities and ScholarshipTopic Modeling

Cited by 59

Provable Limitations of Acquiring Meaning from Ungrounded Form: What Will Future Language Models Understand?

Merrill, W., Goldberg, Y., Schwartz, R., & Smith, N. A. (2021) · Transactions of the Association for Computational Linguistics

Syntax, Semantics, Linguistic VariationLogic, Reasoning, and Knowledge

Cited by 44

Clever Hans or Neural Theory of Mind? Stress Testing Social Reasoning in Large Language Models

Shapira, N., Levy, M., Alavi, S. H., Zhou, X., Choi, Y., Goldberg, Y., Sap, M., & Shwartz, V. (2024) · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)

Child and Animal Learning DevelopmentTopic Modeling

Cited by 44