2 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
The Necessity of Setting Temperature in LLM-as-a-Judge
Lujun Li, Lama Sleem, Yangjie Xu +4
Large Language Models (LLMs) are increasingly used as automated judges, yet decoding temperature is often set by intuition rather than evidence. We run over one million large scale…
Do Large Language Models Grasp The Grammar? Evidence from Grammar-Book-Guided Probing in Luxembourgish
Lujun Li, Yewei Song, Lama Sleem +7
Grammar refers to the system of rules that governs the structural organization and the semantic relations among linguistic units such as sentences, phrases, and words within a give…
Small Language Models in the Real World: Insights from Industrial Text Classification
Lujun Li, Lama Sleem, Niccolo' Gentile +2
With the emergence of ChatGPT, Transformer models have significantly advanced text classification and related tasks. Decoder-only models such as Llama exhibit strong performance an…
Exploring the Impact of Temperature on Large Language Models:Hot or Cold?
Lujun Li, Lama Sleem, Niccolo' Gentile +2
The sampling temperature, a critical hyperparameter in large language models (LLMs), modifies the logits before the softmax layer, thereby reshaping the distribution of output toke…
Is Small Language Model the Silver Bullet to Low-Resource Languages Machine Translation?
Yewei Song, Lujun Li, Cedric Lothritz +6
Low-resource languages (LRLs) lack sufficient linguistic resources and are underrepresented in benchmark datasets, resulting in persistently lower translation quality than high-res…