2 papers
cs.AI2026
SMoE: An Algorithm-System Co-Design for Pushing MoE to the Edge via Expert Substitution
Guoying Zhu, Meng Li, Haipeng Dai +6
The Mixture of Experts (MoE) architecture has emerged as a key technique for scaling Large Language Models by activating only a subset of experts per query. Deploying MoE on consum…
cs.CL2026
Autoencoding-Free Context Compression for LLMs via Contextual Semantic Anchors
Xin Liu, Runsong Zhao, Pengcheng Huang +7
Context compression is an advanced technique that accelerates large language model (LLM) inference by converting long inputs into compact representations. Existing methods primaril…