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Eleonora Presani

2 accepted papers

2023

ROBBIE: Robust Bias Evaluation of Large Generative Language Models

EMNLP 2023long main

As generative large language models (LLMs) grow more performant and prevalent, we must develop comprehensive enough tools to measure and improve their fairness. Different prompt-based datasets can be used to measure social bias across multiple text domains and demographic axes, meaning that testing…

Cited by 0SourceScholar
2022

“I’m sorry to hear that”: Finding New Biases in Language Models with a Holistic Descriptor Dataset

EMNLP 2022main

As language models grow in popularity, it becomes increasingly important to clearly measure all possible markers of demographic identity in order to avoid perpetuating existing societal harms. Many datasets for measuring bias currently exist, but they are restricted in their coverage of demographic…