Search papers, labs, and topics across Lattice.
2
0
4
DiT-Pruning achieves unprecedented image quality retention in Diffusion Transformers, maintaining a CLIP score loss of only 0.001 at 50% sparsity.
Achieve superior LLM pruning performance by first nudging models toward sparsity-friendliness *before* applying any weight removal.
