all AI news
ViLLM-Eval: A Comprehensive Evaluation Suite for Vietnamese Large Language Models
April 18, 2024, 4:46 a.m. | Trong-Hieu Nguyen, Anh-Cuong Le, Viet-Cuong Nguyen
cs.CL updates on arXiv.org arxiv.org
Abstract: The rapid advancement of large language models (LLMs) necessitates the development of new benchmarks to accurately assess their capabilities. To address this need for Vietnamese, this work aims to introduce ViLLM-Eval, the comprehensive evaluation suite designed to measure the advanced knowledge and reasoning abilities of foundation models within a Vietnamese context. ViLLM-Eval consists of multiple-choice questions and predict next word tasks spanning various difficulty levels and diverse disciplines, ranging from humanities to science and engineering. …
abstract advanced advancement arxiv benchmarks capabilities cs.ai cs.cl development evaluation knowledge language language models large language large language models llms reasoning type work
More from arxiv.org / cs.CL updates on arXiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Senior Data Engineer
@ Quantexa | Sydney, New South Wales, Australia
Staff Analytics Engineer
@ Warner Bros. Discovery | NY New York 230 Park Avenue South