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20182026
most citedAttenuating Bias in Word Vectors

98 citations · 123 across the 19 of their papers we have counts for

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Showing 2024 · cs.CLShow all

5 papers · 2 filters

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024

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…