[r/ML] [R] KALAVAI: Predicting When Independent Specialist Fusion Works (gain = 0.82 × divergence − 2.72, R² = 0.856, tested 410M–6.9B)

Summary

KALAVAI introduces a method for predicting the effectiveness of fusing independently fine-tuned AI models. It involves taking a base model, allowing multiple parties to fine-tune it on their specific domains without communication, and then training a lightweight Mixture of Experts (MoE) router to combine these specialized checkpoints. The research provides a formula (gain = 0.82 × divergence − 2.72, R² = 0.856) to predict the performance gain from this independent specialist fusion, tested on models ranging from 410M to 6.9B parameters.

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