Author

Palaash Goel

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Preprint Aug 2026

Unifying Depth and Width Pruning for LLMs via Binary Knapsack Optimization

SNIPER is presented, a two-stage structured pruning framework that solves a knapsack optimization over coarse-granularity components to yield conditionally optimal parameter allocations with respect to fixed importance estimates, followed by a fine-grained pruning stage to meet strict budget constraints.

Palaash Goel, Ayan Sengupta, A. Nambi et al. · 0 citations

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 awa...

Palaash Goel, Ayush Maheshwari, Tanmoy Chakraborty · arXiv.org · 1 citation