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cs.LG2025
A Mathematical Theory of Top- Sparse Attention via Total Variation Distance
Georgios Tzachristas, Lei Deng, Ioannis Tzachristas +2
We develop a unified mathematical framework for certified Top- attention truncation that quantifies approximation error at both the distribution and output levels. For a single…
cs.LG2025
HATA: Trainable and Hardware-Efficient Hash-Aware Top-k Attention for Scalable Large Model Inference
Ping Gong, Jiawei Yi, Shengnan Wang +13
Large Language Models (LLMs) have emerged as a pivotal research area, yet the attention module remains a critical bottleneck in LLM inference, even with techniques like KVCache to…