98 citations · 121 across the 18 of their papers we have counts for
6 papers · 1 filter
GeniL: A Multilingual Dataset on Generalizing Language
Aida Mostafazadeh Davani, Sagar Gubbi, Sunipa Dev +2
Generative language models are transforming our digital ecosystem, but they often inherit societal biases, for instance stereotypes associating certain attributes with specific ide…
Naive Bayes-based Context Extension for Large Language Models
Jianlin Su, Murtadha Ahmed, Wenbo +3
Large Language Models (LLMs) have shown promising in-context learning abilities. However, conventional In-Context Learning (ICL) approaches are often impeded by length limitations…
SeeGULL Multilingual: a Dataset of Geo-Culturally Situated Stereotypes
Mukul Bhutani, Kevin Robinson, Vinodkumar Prabhakaran +2
While generative multilingual models are rapidly being deployed, their safety and fairness evaluations are largely limited to resources collected in English. This is especially pro…
Assessing biomedical knowledge robustness in large language models by query-efficient sampling attacks
R. Patrick Xian, Alex J. Lee, Satvik Lolla +4
The increasing depth of parametric domain knowledge in large language models (LLMs) is fueling their rapid deployment in real-world applications. Understanding model vulnerabilitie…
MiTTenS: A Dataset for Evaluating Gender Mistranslation
Kevin Robinson, Sneha Kudugunta, Romina Stella +2
Translation systems, including foundation models capable of translation, can produce errors that result in gender mistranslation, and such errors can be especially harmful. To meas…
ViSAGe: A Global-Scale Analysis of Visual Stereotypes in Text-to-Image Generation
Akshita Jha, Vinodkumar Prabhakaran, Remi Denton +5
Recent studies have shown that Text-to-Image (T2I) model generations can reflect social stereotypes present in the real world. However, existing approaches for evaluating stereotyp…