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cs.CL2026
SparDA: Sparse Decoupled Attention for Efficient Long-Context LLM Inference
Yaosheng Fu, Guangxuan Xiao, Xin Dong +2
Sparse attention reduces compute and memory bandwidth for long-context LLM inference. However, two key challenges remain: (1) KV cache capacity still grows with sequence length, an…
cs.CL2024
Long Context Alignment with Short Instructions and Synthesized Positions
Wenhao Wu, Yizhong Wang, Yao Fu +3
Effectively handling instructions with extremely long context remains a challenge for Large Language Models (LLMs), typically necessitating high-quality long data and substantial c…