Testing Semantic Importance via Betting

Jacopo Teneggi, Jeremias Sulam
2/3/2026

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Abstract

Recent works have extended notions of feature importance to semantic concepts that are inherently interpretable to the users interacting with a black-box predictive model. Yet, precise statistical guarantees such as false positive rate and false discovery rate control are needed to communicate findings transparently, and to avoid unintended consequences in real-world scenarios. In this paper, we formalize the global (i

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Cite this paper

@article{teneggi2026testing,
  title  = {Testing Semantic Importance via Betting},
  author = {Jacopo Teneggi and Jeremias Sulam},
  year   = {2026},
  doi    = {10.52202/079017-2435},
  url    = {https://doi.org/10.52202/079017-2435},
  journal = {NEURIPS 2024 2024}
}

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