Work

Characterizing the Accuracy-Efficiency Trade-off of Low-rank Decomposition in Language Models

Year: 2024

Type: conference-paper

Source: IEEE International Symposium on Workload Characterization

DOI: 10.1109/iiswc63097.2024.00026

Authors: Chakshu Moar, Faraz Tahmasebi, Michael Pellauer, Hyoukjun Kwon

Institutions: University of California, Irvine, Nvidia (United States)

Language: English

Topic: Advanced Neural Network Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W4406265638

FWCI: 0.458

Cites:

Cited by: 2

Related to: 10