Block selection in large language models solved with the Ising model

The research transforms the pruning of transformer blocks into an energy minimization problem that models magnetic spin interactions. This approach improves deep compression performance by increasing the MMLU score by nearly 23 points compared to competing methods at a 50% compression level in the Llama-3.3-70B model.