Leoma Team Discusses Rank-2 Model Convergence

Team member clarified that Leoma's rank-2 model is unlikely to be rank-1 plus noise, since noise degrades performance and carries no reward incentive. Convergence to similar quality more likely reflects independent parallel training or earlier variants of the same approach. Discussion included model architecture questions about fixed sizing.

• •Rank-2 model probably independent training, not rank-1 derivative
• •Noise penalty rules out simple fork hypothesis
• •Compare HF SHAs to verify repo relationship