Research map / Architectures and efficiency / Pruning and efficient tuning
Bi-directional Masks for Efficient N:M Sparse Training
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- BAME: Block-Aware Mask Evolution for Efficient N:M Sparse Training (ICML 2025 · similarity 0.87)
- TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks (NeurIPS 2025 · similarity 0.87)
- Sparser, Better, Deeper, Stronger: Improving Static Sparse Training with Exact Orthogonal Initialization (ICML 2024 · similarity 0.86)
- S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-training (NeurIPS 2024 · similarity 0.84)
- Advancing Dynamic Sparse Training by Exploring Optimization Opportunities (ICML 2024 · similarity 0.84)
- Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency (ICML 2024 · similarity 0.83)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
