Ayush Maheshwari
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126
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NLP×1
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2026
It Takes a MAESTRO To Prune Bad Experts
MAESTRO is a structured pruning framework designed for MoE language models that models autoregressive expert activation trajectories as Ergodic Markov chains, yielding a globally aware importance heuristic, outperforming state-of-the-art baselines by up to 10.61% in average performance retention under a strict 50% compression regime.
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