4 papers · 1 filter
Measuring Stereotype and Deviation Biases in Large Language Models
Daniel Wang, Eli Brignac, Minjia Mao +1
Large language models (LLMs) are widely applied across diverse domains, raising concerns about their limitations and potential risks. In this study, we investigate two types of bia…
KG2QA: Knowledge Graph-enhanced Retrieval-augmented Generation for Communication Standards Question Answering
Zhongze Luo, Weixuan Wan, Tianya Zhang +2
The rapid evolution of communication technologies has led to an explosion of standards, rendering traditional expert-dependent consultation methods inefficient and slow. To address…
Fine Tuning Methods for Low-resource Languages
Tim Bakkenes, Daniel Wang, Anton Johansson
The rise of Large Language Models has not been inclusive of all cultures. The models are mostly trained on English texts and culture which makes them underperform in other language…
A Systematic Review on Prompt Engineering in Large Language Models for K-12 STEM Education
Eason Chen, Danyang Wang, Luyi Xu +3
Large language models (LLMs) have the potential to enhance K-12 STEM education by improving both teaching and learning processes. While previous studies have shown promising result…