Jun Zhu

Ditch the stochasticity: Deterministic pruning slashes LLM size with minimal performance loss, outperforming stochastic methods and accelerating inference.

Achieve state-of-the-art video compression with a surprisingly compact architecture by recursively applying a shared channel mixing module across scales in implicit neural representations.