What are sparsity techniques in neural NLP models?

Sparsity reduces computation by activating only a subset of model weights or neurons.

Sparse models use techniques like pruning, sparse attention, and MoE routing to reduce computation. This improves efficiency while maintaining performance but introduces challenges in hardware optimization and training stability.