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$μ$-MoE: Test-Time Pruning as Micro-Grained Mixture-of-Experts

μμ-MoE: Test-Time Pruning as Micro-Grained Mixture-of-Experts

T. Koike-Akino
Jing Liu
Ye Wang
    MoE
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Papers citing "$μ$-MoE: Test-Time Pruning as Micro-Grained Mixture-of-Experts"

3 / 3 papers shown
Title
Quantum-PEFT: Ultra parameter-efficient fine-tuning
Toshiaki Koike-Akino
F. Tonin
Yongtao Wu
Frank Zhengqing Wu
Leyla Naz Candogan
Volkan Cevher
MQ
331
6
0
07 Mar 2025
Dynamic DropConnect: Enhancing Neural Network Robustness through Adaptive Edge Dropping Strategies
Dynamic DropConnect: Enhancing Neural Network Robustness through Adaptive Edge Dropping Strategies
Yuan-Chih Yang
Hung-Hsuan Chen
105
1
0
27 Feb 2025
Q-VLM: Post-training Quantization for Large Vision-Language Models
Q-VLM: Post-training Quantization for Large Vision-Language Models
Changyuan Wang
Ziwei Wang
Xiuwei Xu
Yansong Tang
Jie Zhou
Jiwen Lu
MQ
202
9
0
10 Oct 2024