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cs.CL2025
HCAttention: Extreme KV Cache Compression via Heterogeneous Attention Computing for LLMs
Dongquan Yang, Yifan Yang, Xiaotian Yu +2
Processing long-context inputs with large language models presents a significant challenge due to the enormous memory requirements of the Key-Value (KV) cache during inference. Exi…
cs.CL2024
Generation Meets Verification: Accelerating Large Language Model Inference with Smart Parallel Auto-Correct Decoding
Hanling Yi, Feng Lin, Hongbin Li +3
This research aims to accelerate the inference speed of large language models (LLMs) with billions of parameters. We propose \textbf{S}mart \textbf{P}arallel \textbf{A}uto-\textbf{…
cs.CL2024
BiTA: Bi-Directional Tuning for Lossless Acceleration in Large Language Models
Feng Lin, Hanling Yi, Hongbin Li +4
Large language models (LLMs) commonly employ autoregressive generation during inference, leading to high memory bandwidth demand and consequently extended latency. To mitigate this…