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cs.HC2025
CafGa: Customizing Feature Attributions to Explain Language Models
Alan Boyle, Furui Cheng, Vilém Zouhar +1
Feature attribution methods, such as SHAP and LIME, explain machine learning model predictions by quantifying the influence of each input component. When applying feature attributi…
cs.HC2024
iToT: An Interactive System for Customized Tree-of-Thought Generation
Alan Boyle, Isha Gupta, Sebastian Hönig +4
As language models have become increasingly successful at a wide array of tasks, different prompt engineering methods have been developed alongside them in order to adapt these mod…