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To Burst or Not to Burst: Generating and Quantifying Improbable Text
While large language models (LLMs) are extremely capable at text generation, their outputs are still distinguishable from human-authored text.
Selecting Shots for Demographic Fairness in Few-Shot Learning with Large Language Models
In this work, we explore the effect of shots, which directly affect the performance of models, on the fairness of LLMs as NLP classification systems.
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