3 citations · 16 across the 42 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2026
KernelClaw: A Multi-Agent Framework for GPU Kernel Optimization with Dual-Memory Mechanisms
Qitong Sun, Jun Han, Tianlin Li +6
Improving GPU kernel efficiency is crucial for efficient AI systems. Recent work has explored leveraging large language models (LLMs) for GPU kernel generation and optimization. Ho…
cs.LG2023★ 1 cited
Robust Multi-Agent Reinforcement Learning by Mutual Information Regularization
Simin Li, Ruixiao Xu, Jingqiao Xiu +4
In multi-agent reinforcement learning (MARL), ensuring robustness against unpredictable or worst-case actions by allies is crucial for real-world deployment. Existing robust MARL m…
cs.LG2023★ 1 cited
On-Chip Hardware-Aware Quantization for Mixed Precision Neural Networks
Wei Huang, Haotong Qin, Yangdong Liu +4
Low-bit quantization emerges as one of the most promising compression approaches for deploying deep neural networks on edge devices. Mixed-precision quantization leverages a mixtur…