84 citations · 90 across the 9 of their papers we have counts for
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cs.CL2025
Unshackling Context Length: An Efficient Selective Attention Approach through Query-Key Compression
Haoyu Wang, Tong Teng, Tianyu Guo +4
Handling long-context sequences efficiently remains a significant challenge in large language models (LLMs). Existing methods for token selection in sequence extrapolation either e…
cs.CL2023★ 1 cited
PanGu-: Enhancing Language Model Architectures via Nonlinearity Compensation
Yunhe Wang, Hanting Chen, Yehui Tang +17
The recent trend of large language models (LLMs) is to increase the scale of both model size (\aka the number of parameters) and dataset to achieve better generative ability, which…