Berant, Jonathan

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569

The Web as a Knowledge-Base for Answering Complex Questions

Talmor, A., & Berant, J. (2018) · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)

Topic ModelingInformation Retrieval and Search Behavior

Cited by 520

Learning To Retrieve Prompts for In-Context Learning

Rubin, O., Herzig, J., & Berant, J. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 374

Transformer Feed-Forward Layers Are Key-Value Memories

Geva, M., Schuster, R., Berant, J., & Levy, O. (2020) · arXiv

Topic ModelingExplainable Artificial Intelligence (XAI)

Cited by 353

Transformer Feed-Forward Layers Are Key-Value Memories

Geva, M., Schuster, R., Berant, J., & Levy, O. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Topic ModelingExplainable Artificial Intelligence (XAI)

Cited by 353

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

Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies

Geva, M., Khashabi, D., Segal, E., Khot, T., Roth, D., & Berant, J. (2021) · Transactions of the Association for Computational Linguistics

Topic ModelingMultimodal Machine Learning Applications

Cited by 242

Coarse-to-Fine Question Answering for Long Documents

Choi, E., Hewlett, D., Uszkoreit, J., Polosukhin, I., Lacoste, A., & Berant, J. (2017) · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 177

Text Segmentation as a Supervised Learning Task

Koshorek, O., Cohen, A., Mor, N., Rotman, M., & Berant, J. (2018) · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 167

BERTese: Learning to Speak to BERT

Haviv, A., Berant, J., & Globerson, A. (2021) · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

Topic ModelingInformation Retrieval and Search Behavior

Cited by 84

Diverse Demonstrations Improve In-context Compositional Generalization

Levy, I., Bogin, B., & Berant, J. (2023) · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 66

Evaluating the Evaluation of Diversity in Natural Language Generation

Tevet, G., & Berant, J. (2021) · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

Natural Language Processing TechniquesTopic Modeling

Cited by 52

Efficient long-text understanding with short-text models

Ivgi, M., Shaham, U., & Berant, J. (2023) · Transactions of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 42

SCROLLS: Standardized CompaRison Over Long Language Sequences

Shaham, U., Segal, E., Ivgi, M., Efrat, A., Yoran, O., Haviv, A., Gupta, A., Xiong, W., Geva, M., Berant, J., et al. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesTopic Modeling

Cited by 40

Answering Questions by Meta-Reasoning over Multiple Chains of Thought

Yoran, O., Wolfson, T., Bogin, B., Katz, U., Deutch, D., & Berant, J. (2023) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 38

Learning to retrieve passages without supervision

Ram, O., Shachaf, G., Levy, O., Berant, J., & Globerson, A. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingInformation Retrieval and Search Behavior

Cited by 35

Making Retrieval-Augmented Language Models Robust to Irrelevant Context

Yoran, O., Wolfson, T., Ram, O., & Berant, J. (2023) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 26

ZeroSCROLLS: A zero-shot benchmark for long text understanding

Shaham, U., Ivgi, M., Efrat, A., Berant, J., & Levy, O. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023

Topic ModelingMultimodal Machine Learning Applications

Cited by 23

ZeroSCROLLS: A Zero-Shot Benchmark for Long Text Understanding

Shaham, U., Ivgi, M., Efrat, A., Berant, J., & Levy, O. (2023) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 23

From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces

Shaw, P., Joshi, M., Cohan, J., Berant, J., Pasupat, P., Hu, H., Khandelwal, U., Lee, K., & Toutanova, K. N. (2023) · Advances in Neural Information Processing Systems 36

Usability and User Interface DesignWeb Data Mining and Analysis

Cited by 12

Evaluating Text GANs as Language Models

Tevet, G., Habib, G., Shwartz, V., & Berant, J. (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)

Topic ModelingNatural Language Processing Techniques

Cited by 12

AssistantBench: Can Web Agents Solve Realistic and Time-Consuming Tasks?

Yoran, O., Amouyal, S. J., Malaviya, C., Bogin, B., Press, O., & Berant, J. (2024) · arXiv

Information Retrieval and Search BehaviorWeb Data Mining and Analysis

Cited by 11

In-Context Learning with Long-Context Models: An In-Depth Exploration

Bertsch, A., Ivgi, M., Xiao, E., Alon, U., Berant, J., Gormley, M. R., & Neubig, G. (2024) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 7