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Flip Rate Lies When the Model Saturates: A Confidence-Stratified Methodology for Deletion-Based XAI Evaluation

This story is from 2026-09-28. It is preserved in the archive; the latest stories are on the live feed.

Deletion-based faithfulness tests ask a simple question. If I remove the token that an explainer considers most important, does the model's prediction change? The rate at which predictions change is called the flip rate . It is often used to evaluate whether an explanation reflects what a model act…

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  1. 2026-09-28 09:12 · DEV Community — Machine Learning
    Flip Rate Lies When the Model Saturates: A Confidence-Stratified Methodology for Deletion-Based XAI Evaluation

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