Sampling for SFT: evaluating post-training

What happened and what to do

In a post published on October 2, 2026, the authors present a method that adds sampling to the post-training stack. They claim the approach could make SFT competitive with current post-training methods, with better generalization and less forgetting in some cases.

A company evaluating SFT and RL can test the approach on representative tasks, compare generalization and forgetting against a baseline, and record results in an evaluation pipeline. This grounds the method choice in evidence from the company’s own use case, without assuming the gains will apply in every scenario.

How the consultancy can help

Wendelmaques can diagnose the evaluation process, define a testing scope for comparing SFT and RL, and implement an experiment, monitoring, and results-analysis pipeline on the company’s infrastructure.

Next step

Send a brief description of your post-training case to receive a proposal scoped for diagnosis and implementation.