4 citations · 11 across the 9 of their papers we have counts for
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cs.CL2024★ 3 cited
SeerAttention: Learning Intrinsic Sparse Attention in Your LLMs
Yizhao Gao, Zhichen Zeng, Dayou Du +8
Attention is the cornerstone of modern Large Language Models (LLMs). Yet its quadratic complexity hinders efficiency and scalability, especially for long-context processing. A prom…
cs.CL2024★ 1 cited
BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation
Dayou Du, Yijia Zhang, Shijie Cao +4
The upscaling of Large Language Models (LLMs) has yielded impressive advances in natural language processing, yet it also poses significant deployment challenges. Weight quantizati…
cs.CL2023
AFPQ: Asymmetric Floating Point Quantization for LLMs
Yijia Zhang, Sicheng Zhang, Shijie Cao +4
Large language models (LLMs) show great performance in various tasks, but face deployment challenges from limited memory capacity and bandwidth. Low-bit weight quantization can sav…