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cs.CL2025
Optimizing Class-Level Probability Reweighting Coefficients for Equitable Prompting Accuracy
Ruixi Lin, Yang You
Even as we engineer LLMs for alignment and safety, they often uncover biases from pre-training data's statistical regularities (from disproportionate co-occurrences to stereotypica…
cs.CL2025
Ensemble Debiasing Across Class and Sample Levels for Fairer Prompting Accuracy
Ruixi Lin, Ziqiao Wang, Yang You
Language models are strong few-shot learners and achieve good overall accuracy in text classification tasks, masking the fact that their results suffer from great class accuracy im…
cs.CL2025
Let the Fuzzy Rule Speak: Enhancing In-context Learning Debiasing with Interpretability
Ruixi Lin, Yang You
Large language models (LLMs) often struggle with balanced class accuracy in text classification tasks using in-context learning (ICL), hindering some practical uses due to user dis…