Papers by Alan David Boyle
CafGa: Customizing Feature Attributions to Explain Language Models (2025.emnlp-demos)
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| Challenge: | Feature attribution methods, such as SHAP and LIME, quantify the influence of each input component in a model. |
| Approach: | They propose a tool for generating and evaluating feature attribution explanations at customizable granularities. |
| Outcome: | The proposed tool is compared with two baseline methods: PartitionSHAP and MExGen. |