2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2026
Communication-Efficient Verifiable Attention for LLM Inference
Ziqun Chen, Ming Wu, Michael Heinrich +4
Computation integrity of remote large language model (LLM) serving can be questionable. For conventional deep neural networks (DNNs), the existing TEE-shielded DNN partitioning (TS…
cs.PF2017★ 2 cited
BENCHIP: Benchmarking Intelligence Processors
Jinhua Tao, Zidong Du, Qi Guo +12
The increasing attention on deep learning has tremendously spurred the design of intelligence processing hardware. The variety of emerging intelligence processors requires standard…