Author

Pieter Delobelle

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#machine learning Preprint Sep 2026

It's All Training: A Fully Synthetic Single-Stage Recipe for LLMs

Current pre-training datasets are derived from web crawls, with all their issues, and were not designed to support mid- and post-training pipelines--for instance, they contain little explicit reasoning. Thus, many frontier labs have begun to develop their own internal datasets, starting from state-of-the-art models, to...

Pierre-Carl Langlais, Pieter Delobelle, Yannick Detrois et al. · 0 citations

#machine learning Conference Jan 2026

Audit Me If You Can: Query-Efficient Active Fairness Auditing of Black-Box LLMs

BAFA, the Bounded Active Fairness Auditor is introduced, the Bounded Active Fairness Auditor for query-efficient auditing of black-box LLMs, suggesting that active sampling can reduce resources needed for independent fairness auditing with LLMs, supporting continuous model evaluations.

David Hartmann, Lena Pohlmann, Lelia Hanslik et al. · Annual Meeting of the Associ... · 7 citations