Author

Ayush Maheshwari

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Preprint Jul 2026

It Takes a MAESTRO To Prune Bad Experts

MAESTRO (Markov-chain Approximated Expert Sparsification via Transition-based ROuting), a structured pruning framework designed for MoE architectures that models autoregressive expert activation trajectories as Ergodic Markov chains whose stationary distributions encode cross-layer dependencies, yielding a globally aware importance heuristic is introduced.

Palaash Goel, Ayush Maheshwari, Tanmoy Chakraborty · 1 citation