SparseSwaps: Efficient LLM Pruning Mask Refinement
Published:Dec 11, 2025 18:47
•1 min read
•ArXiv
Analysis
The SparseSwaps method, as described in the ArXiv paper, tackles the challenge of refining pruning masks for large language models. The paper likely introduces a novel approach to improve the efficiency and effectiveness of LLM pruning at scale.
Key Takeaways
Reference
“SparseSwaps likely offers a new approach to mask refinement within the LLM pruning process.”