Efrat, Avia

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

LIMA: Less Is More for Alignment

Zhou, C., Liu, P., Xu, P., Iyer, S., Sun, J., Mao, Y., Ma, X., Efrat, A., Yu, P., Yu, L., et al. (2023) · Advances in Neural Information Processing Systems 36

Domain Adaptation and Few-Shot LearningEducational Assessment and Pedagogy

Cited by 275

LIMA: Less Is More for Alignment

Zhou, C., Liu, P., Xu, P., Iyer, S., Sun, J., Mao, Y., Ma, X., Efrat, A., Yu, P., Yu, L., et al. (2023) · arXiv

Domain Adaptation and Few-Shot LearningEducational Assessment and Pedagogy

Cited by 275

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