Author

Samira Ebrahimi Kahou

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#artificial intelligence Preprint Sep 2026

Beyond Rule-Based Mutation Testing: Test-Aware Mutant Generation Using Large Language Models

Mutation testing evaluates test-suite adequacy by injecting synthetic faults into program code. However, traditional rule-based tools often generate large numbers of trivial, redundant, or equivalent mutants that limit their practical use for identifying gaps in a test suite. While recent large language model (LLM)-bas...

Nils Kiele, Zainab Saad, Zi-Rui Wang et al. · 0 citations

Preprint Aug 2026

Training Fair Tabular Foundation Models

Tabular Foundation Models (TFMs) have emerged as leading methods for tabular predictive tasks, leveraging in-context learning to predict on new data without task-specific training. Despite the increased use of TFMs in high-stakes decision-making, their fairness properties remain largely unexplored. In this work, we inc...

P. Kenfack, Jesse C. Cresswell, Anthony L. Caterini et al. · 0 citations