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cs.DC2026
Recency/Frequency Adaptive KV Caching for Large Language Model Serving
Yang Shen, Meghana Madhyastha, Robert Underwood +2
Key-value (KV) caching is a powerful technique for accelerating large language model inference and generation. Inference workloads are large and diverse, which makes them difficult…
cs.DC2025
On Harnessing Idle Compute at the Edge for Foundation Model Training
Leyang Xue, Meghana Madhyastha, Myungjin Lee +3
The foundation-model ecosystem remains highly centralized because training requires immense compute resources and is therefore largely limited to large cloud operators. Edge-assist…
cs.DC2024
Edge-Parallel Graph Encoder Embedding
Ariel Lubonja, Cencheng Shen, Carey Priebe +1
New algorithms for embedding graphs have reduced the asymptotic complexity of finding low-dimensional representations. One-Hot Graph Encoder Embedding (GEE) uses a single, linear p…