3 citations · 3 across the 3 of their papers we have counts for
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cs.AR2026
A Shape-Adaptive Architecture with Disaggregated Quantization for Efficient LLM Serving
Cong Guo, Chiyue Wei, Bowen Duan +5
Large language models (LLMs) have become the backbone of modern AI applications, but pose significant challenges for efficient inference. Their autoregressive generation divides ex…
cs.AR2025
CAMformer: Associative Memory is All You Need
Tergel Molom-Ochir, Benjamin F. Morris, Mark Horton +8
Transformers face scalability challenges due to the quadratic cost of attention, which involves dense similarity computations between queries and keys. We propose CAMformer, a nove…
cs.AR2024★ 3 cited
A Survey: Collaborative Hardware and Software Design in the Era of Large Language Models
Cong Guo, Feng Cheng, Zhixu Du +21
The rapid development of large language models (LLMs) has significantly transformed the field of artificial intelligence, demonstrating remarkable capabilities in natural language…