Multiverse Computing: Ising block pruning beats baseline by ~23 MMLU
Multiverse Computing’s Sept 21 Hugging Face write-up models transformer-block deletion as an Ising optimization problem so candidates can be scored without rebuilding each pruned model. On Llama-3.3-70B-Instruct with 40 of 80 blocks removed and no retrain, it scored 76.9 MMLU vs 54.0 for a block-influence baseline (original 82.2); GitHub code is patent-pending and research/non-commercial only.