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Counterfactual Marginalisation: Framework for Evaluating Robustness to Nuisance Variables

This story is from 2026-09-11. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.10778v1 Announce Type: new Abstract: Machine learning models can achieve strong test performance while relying on demographic or acquisition-related shortcuts. We propose counterfactual (CF) marginalisation as a test-time evaluation procedure for assessing robustness of classification mo…

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  1. 2026-09-11 04:00 · arXiv cs.LG
    Counterfactual Marginalisation: Framework for Evaluating Robustness to Nuisance Variables

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