Work

Scaling Laws and Efficient Inference for Ternary Language Models

Year: 2025

Type: conference-paper

Abstract: Tejas Vaidhya, Ayush Kaushal, Vineet Jain, Francis Couture-Harpin, Prashant Shishodia, Majid Behbahani, Yuriy Nevmyvaka, Irina Rish. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2025.

Source: Annual Meeting of the Association for Computational Linguistics (ACL)

DOI: 10.18653/v1/2025.acl-long.1294

Authors: Tejas Vaidhya, Ayush Kaushal, Vineet Jain, Francis Couture-Harpin, Prashant Shishodia, Majid Behbahani, Yuriy Nevmyvaka, Irina Rish

Institutions: Mila - Quebec Artificial Intelligence Institute, Université de Montréal, McGill University, Université du Québec, École de Technologie Supérieure, Morgan Stanley (United States)

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: U.S. Department of Energy, Canadian Institute for Advanced Research, Canada Excellence Research Chairs, Government of Canada, Office of Science, Oak Ridge National Laboratory

OpenAlex ID: W4412889913

FWCI: 1.059

Cites:

Cited by: 1

Related to: 10