2 papers
cs.DC2026
Collective Communication for Distributed LLM Systems: Planning, Runtime Adaptation, and Computation Coordination
Xuebin Song, Menghao Zhang, Yuezheng Liu +5
Distributed large language model (LLM) systems increasingly rely on collective communication primitives such as AllReduce (AR), ReduceScatter (RS), AllGather (AG), and AlltoAll (A2…
cs.SE2025
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Mingzhe Du, Luu Anh Tuan, Yue Liu +6
Large Language Models (LLMs) generate functionally correct solutions but often fall short in code efficiency, a critical bottleneck for real-world deployment. In this paper, we int…