Non‐Autoregressive Translation Algorithm Based on LLM Knowledge Distillation in English Corpus
ABSTRACT Although significant advancements have been made in the quality of machine translation by large‐scale language models, their high computational costs and resource consumption have hindered their widespread adoption in practical applications. So this research introduces an English corpus‐bas...
Saved in:
Main Authors: | Fang Ju, Weihui Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2025-01-01
|
Series: | Engineering Reports |
Subjects: | |
Online Access: | https://doi.org/10.1002/eng2.13077 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Corpus-based translation research: its development and implications for general, literary and Bible translation
by: A. Kruger
Published: (2002-06-01) -
Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing
by: Arief Setyanto, et al.
Published: (2025-01-01) -
Advancing Model Explainability: Visual Concept Knowledge Distillation for Concept Bottleneck Models
by: Ju-Hwan Lee, et al.
Published: (2025-01-01) -
Assessment-Based Optimization of Distillation Parameters
by: Ludmila N. Krikunova, et al.
Published: (2023-06-01) -
Predicting Subsurface Layer Thickness and Seismic Wave Velocity Using Deep Learning: Knowledge Distillation Approach
by: Amir Moslemi, et al.
Published: (2025-01-01)