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cs.LG2026
Joint Encoding of KV-Cache Blocks for Scalable LLM Serving
Joseph Kampeas, Emir Haleva
Modern large language models (LLMs) drive interactive AI systems but are bottlenecked by the memory-heavy growth of key-value (KV) caches, which limits real-time throughput under c…
cs.LG2023★ 2 cited
Linear Log-Normal Attention with Unbiased Concentration
Yury Nahshan, Joseph Kampeas, Emir Haleva
Transformer models have achieved remarkable results in a wide range of applications. However, their scalability is hampered by the quadratic time and memory complexity of the self-…
cs.LG2023
Rotation Invariant Quantization for Model Compression
Joseph Kampeas, Yury Nahshan, Hanoch Kremer +4
Post-training Neural Network (NN) model compression is an attractive approach for deploying large, memory-consuming models on devices with limited memory resources. In this study,…