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cs.CL2025
Quantifying and Mitigating Selection Bias in LLMs: A Transferable LoRA Fine-Tuning and Efficient Majority Voting Approach
Blessed Guda, Lawrence Francis, Gabrial Zencha Ashungafac +2
Multiple Choice Question (MCQ) answering is a widely used method for evaluating the performance of Large Language Models (LLMs). However, LLMs often exhibit selection bias in MCQ t…
cs.CL2025
QMOS: Enhancing LLMs for Telecommunication with Question Masked loss and Option Shuffling
Blessed Guda, Gabrial Zencha Ashungafac, Lawrence Francis +1
Large Language models (LLMs) have brought about substantial advancements in the field of Question Answering (QA) systems. These models do remarkably well in addressing intricate in…