5 papers · 1 filter
D-Score: A Spectral Hidden-State Signal for Hallucination Detection in Large Language Models
Bianca Raimondi, Davide Evangelista, Maurizio Gabbrielli +1
Large Language Models can produce fluent text that is false, unsupported by the available evidence, or inconsistent with information that appears to be internally represented by th…
The CompMath-MCQ Dataset: Are LLMs Ready for Higher-Level Math?
Bianca Raimondi, Francesco Pivi, Davide Evangelista +1
The evaluation of Large Language Models (LLMs) on mathematical reasoning has largely focused on elementary problems, competition-style questions, or formal theorem proving, leaving…
Analysing Moral Bias in Finetuned LLMs through Mechanistic Interpretability
Bianca Raimondi, Daniela Dalbagno, Maurizio Gabbrielli
Large language models (LLMs) have been shown to internalize human-like biases during finetuning, yet the mechanisms by which these biases manifest remain unclear. In this work, we…
Exploiting Primacy Effect To Improve Large Language Models
Bianca Raimondi, Maurizio Gabbrielli
Large Language Models (LLMs) have become essential in many Natural Language Processing (NLP) tasks, leveraging extensive pre-training and fine-tuning to achieve high accuracy. Howe…
Affordably Fine-tuned LLMs Provide Better Answers to Course-specific MCQs
Bianca Raimondi, Saverio Giallorenzo, Maurizio Gabbrielli
In education, the capability of generating human-like text of Large Language Models (LLMs) inspired work on how they can increase the efficiency of learning and teaching. We study…