Human Review for Post-Training Improvement of Low-Resource Language Performance in Large Language Models
Author:
Affiliation:
1. Dimagi, Inc.,USA
2. Dimagi, Inc.,Malawi
3. Pachi,Malawi
Funder
Bill & Melinda Gates Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10628445/10628534/10628927.pdf?arnumber=10628927
Reference24 articles.
1. Emergent Abilities of Large Language Models;Wei;Trans. Mach. Learn. Res.,2022
2. Application of Large Language Models to Software Engineering Tasks: Opportunities, Risks, and Implications
3. Understanding the Benefits and Challenges of Deploying Conversational AI Leveraging Large Language Models for Public Health Intervention
4. Evaluating Large Language Models for Sentence Augmentation in Low-Resource Languages: A Case Study on Kazakh
5. Pluralizing Nouns across Agglutinating Bantu Languages;Byamugisha,2024
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