1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.DC2026
Surviving Partial Rank Failures in Wide Expert-Parallel MoE Inference
Xun Sun, Shaoyuan Chen, Pingchuan Ma +18
Mixture-of-Experts (MoE) serving relies on wide expert parallelism (EP) to aggregate the memory capacity and bandwidth of many GPUs within one inference instance. This efficiency c…
cs.LG2025★ 1 cited
Efficient Modular Learning through Naive LoRA Summation: Leveraging Orthogonality in High-Dimensional Models
Zhanhao Cao, Clement Truong, Andrew Lizarraga
Recent advances in large language models are driven by scale, while parameter-efficient fine-tuning (PEFT) enables updating only a small fraction of parameters. Low-Rank Adaptation…