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Marco Basaldella

2 accepted papers

2024

LUQ: Long-text Uncertainty Quantification for LLMs

EMNLP 2024main

Large Language Models (LLMs) have demonstrated remarkable capability in a variety of NLP tasks. However, LLMs are also prone to generate nonfactual content. Uncertainty Quantification (UQ) is pivotal in enhancing our understanding of a model’s confidence on its generation, thereby aiding in the miti…

2021

Self-Alignment Pretraining for Biomedical Entity Representations

NAACL 2021long

Despite the widespread success of self-supervised learning via masked language models (MLM), accurately capturing fine-grained semantic relationships in the biomedical domain remains a challenge. This is of paramount importance for entity-level tasks such as entity linking where the ability to model…