Ivgi, Maor

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

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

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