Author

Ignacio Hounie

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Preprint Jul 2026

Every Sample Counts: Supervised Fine-Tuning of Language Models with Pointwise Constraints

This work proposes a novel alignment framework that addresses the gap between per-sample constraints and average loss by enforcing per-sample constraints while still minimizing an average loss, and develops an augmented Lagrangian approach tailored to this formulation.

Ignacio Hounie, Ignacio Boero, A. Ribeiro · 2 citations