Papers by Jeffrey Friedman

1 papers
Robust Explanations for User Trust in Enterprise NLP Systems (2026.acl-industry)

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Challenge: Existing studies on explanation stability under real user noise are limited . decoder LLMs produce significantly more stable explanations than encoder baselines .
Approach: They propose a black-box robustness evaluation framework for token-level explanations based on leave-one-out occlusion . they propose to operationalize explanation robustness with top-token flip rate under realistic perturbations at multiple severity levels .
Outcome: The proposed framework is compared with baseline models and encoder and decoder families.

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