4 papers · 1 filter
SLMEval: Entropy-Based Calibration for Human-Aligned Evaluation of Large Language Models
Roland Daynauth, Christopher Clarke, Krisztian Flautner +2
The LLM-as-a-Judge paradigm offers a scalable, reference-free approach for evaluating language models. Although several calibration techniques have been proposed to better align th…
Ranking Unraveled: Recipes for LLM Rankings in Head-to-Head AI Combat
Roland Daynauth, Christopher Clarke, Krisztian Flautner +2
Deciding which large language model (LLM) to use is a complex challenge. Pairwise ranking has emerged as a new method for evaluating human preferences for LLMs. This approach entai…
PEFT-U: Parameter-Efficient Fine-Tuning for User Personalization
Christopher Clarke, Yuzhao Heng, Lingjia Tang +1
The recent emergence of Large Language Models (LLMs) has heralded a new era of human-AI interaction. These sophisticated models, exemplified by Chat-GPT and its successors, have ex…
Guylingo: The Republic of Guyana Creole Corpora
Christopher Clarke, Roland Daynauth, Charlene Wilkinson +2
While major languages often enjoy substantial attention and resources, the linguistic diversity across the globe encompasses a multitude of smaller, indigenous, and regional langua…