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cs.LG2026
Fine-Grained Benchmark Generation for Comprehensive Evaluation of Foundation Models
Mohammed Saidul Islam, Negin Baghbanzadeh, Farnaz Kohankhaki +5
Evaluation of foundation models often rely on aggregate scores from benchmarks that lack comprehensive coverage and metadata for a fine-grained evaluation. We introduce a framework…
cs.LG2025
A Flexible Fairness Framework with Surrogate Loss Reweighting for Addressing Sociodemographic Disparities
Wen Xu, Elham Dolatabadi
This paper presents a new algorithmic fairness framework called - Fair Machine Learning (- FML), designed to optimize fairne…