2 papers
cs.CL2025
Investigating the Capabilities and Limitations of Machine Learning for Identifying Bias in English Language Data with Information and Heritage Professionals
Lucy Havens, Benjamin Bach, Melissa Terras +1
Despite numerous efforts to mitigate their biases, ML systems continue to harm already-marginalized people. While predominant ML approaches assume bias can be removed and fair mode…
cs.CL2024
Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain
Aryo Pradipta Gema, Pasquale Minervini, Luke Daines +2
Adapting pretrained language models to novel domains, such as clinical applications, traditionally involves retraining their entire set of parameters. Parameter-Efficient Fine-Tuni…