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cs.LG2025
vAttention: Verified Sparse Attention
Aditya Desai, Kumar Krishna Agrawal, Shuo Yang +5
State-of-the-art sparse attention methods for reducing decoding latency fall into two main categories: approximate top- (and its extension, top-) and recently introduced samp…
cs.LG2025
SLA: Beyond Sparsity in Diffusion Transformers via Fine-Tunable Sparse-Linear Attention
Jintao Zhang, Haoxu Wang, Kai Jiang +10
In Diffusion Transformer (DiT) models, particularly for video generation, attention latency is a major bottleneck due to the long sequence length and the quadratic complexity. We f…
cs.LG2025
Twilight: Adaptive Attention Sparsity with Hierarchical Top- Pruning
Chaofan Lin, Jiaming Tang, Shuo Yang +6
Leveraging attention sparsity to accelerate long-context large language models (LLMs) has been a hot research topic. However, current algorithms such as sparse attention or key-val…