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20222026
most citedAuto-ViT-Acc: An FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization

6 citations · 15 across the 14 of their papers we have counts for

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2 papers · 1 filter

cs.AI2026

UniMoMo: Expert Merging-Based MoE Acceleration for Large Recommendation Models

Lei Xin, Bin Gu, Peize Li +8

Sparse mixture-of-experts (MoE) layers expand recommendation capacity through conditional computation, yet a trained checkpoint still stores and routes over its full expert bank. W…

cs.AI2025

Collaborative Compression for Large-Scale MoE Deployment on Edge

Yixiao Chen, Yanyue Xie, Ruining Yang +6

The Mixture of Experts (MoE) architecture is an important method for scaling Large Language Models (LLMs). It increases model capacity while keeping computation cost low. However,…