mlsanityData to 14 Oct 2026

DetoxAI: a Python Toolkit for Debiasing Deep Learning Models in Computer Vision

arXiv 2505.05492 ↗First posted 2 May 2025cs.CV cs.AI cs.LGcited by 1

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Abstract (arXiv)

While machine learning fairness has made significant progress in recent years, most existing solutions focus on tabular data and are poorly suited for vision-based classification tasks, which rely heavily on deep learning. To bridge this gap, we introduce DetoxAI, an open-source Python library for improving fairness in deep learning vision classifiers through post-hoc debiasing. DetoxAI implements state-of-the-art debiasing algorithms, fairness metrics, and visualization tools. It supports debiasing via interventions in internal representations and includes attribution-based visualization tools and quantitative algorithmic fairness metrics to show how bias is mitigated. This paper presents the motivation, design, and use cases of DetoxAI, demonstrating its tangible value to engineers and researchers.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 3 of its 7 references that are in the map. First posted on arXiv 2 May 2025.

Builds on

3 of 7 references.

References · 3

  1. 2019A Survey on Bias and Fairness in Machine Learningcited by 1,917
  2. 2023LEACE: Perfect linear concept erasure in closed formcited by 267
  3. 2020Intra-Processing Methods for Debiasing Neural Networkscited by 27

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.