Estimating Knowledge in Large Language Models Without Generating a Single Token

Daniela Gottesman, Mor Geva


Anthology ID:
2024.emnlp-main.232
Volume:
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2024
Address:
Miami, Florida, USA
Editors:
Yaser Al-Onaizan, Mohit Bansal, Yun-Nung Chen
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3994–4019
Language:
URL:
https://aclanthology.org/2024.emnlp-main.232
DOI:
10.18653/v1/2024.emnlp-main.232
Bibkey:
Cite (ACL):
Daniela Gottesman and Mor Geva. 2024. Estimating Knowledge in Large Language Models Without Generating a Single Token. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 3994–4019, Miami, Florida, USA. Association for Computational Linguistics.
Cite (Informal):
Estimating Knowledge in Large Language Models Without Generating a Single Token (Gottesman & Geva, EMNLP 2024)
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PDF:
https://aclanthology.org/2024.emnlp-main.232.pdf