Poster "mixture of experts" Papers
52 papers found • Page 1 of 2
Conference
CryptoMoE: Privacy-Preserving and Scalable Mixture of Experts Inference via Balanced Expert Routing
Yifan Zhou, Tianshi Xu, Jue Hong et al.
Dense2MoE: Restructuring Diffusion Transformer to MoE for Efficient Text-to-Image Generation
Youwei Zheng, Yuxi Ren, Xin Xia et al.
Drop-Upcycling: Training Sparse Mixture of Experts with Partial Re-initialization
Taishi Nakamura, Takuya Akiba, Kazuki Fujii et al.
Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts
Guorui Zheng, Xidong Wang, Juhao Liang et al.
Equipping Vision Foundation Model with Mixture of Experts for Out-of-Distribution Detection
Shizhen Zhao, Jiahui Liu, Xin Wen et al.
Graph Sparsification via Mixture of Graphs
Guibin Zhang, Xiangguo SUN, Yanwei Yue et al.
GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning
Haonan Yuan, Qingyun Sun, Junhua Shi et al.
HMoRA: Making LLMs More Effective with Hierarchical Mixture of LoRA Experts
Mengqi Liao, Wei Chen, Junfeng Shen et al.
HMVLM:Human Motion-Vision-Language Model via MoE LoRA
Lei Hu, Yongjing Ye, Shihong Xia
Instruction-Grounded Visual Projectors for Continual Learning of Generative Vision-Language Models
Hyundong Jin, Hyung Jin Chang, Eunwoo Kim
Intrinsic User-Centric Interpretability through Global Mixture of Experts
Vinitra Swamy, Syrielle Montariol, Julian Blackwell et al.
JanusDNA: A Powerful Bi-directional Hybrid DNA Foundation Model
Qihao Duan, Bingding Huang, Zhenqiao Song et al.
Learning to Specialize: Joint Gating-Expert Training for Adaptive MoEs in Decentralized Settings
Yehya Farhat, Hamza ElMokhtar Shili, Fangshuo Liao et al.
LLaVA-MoD: Making LLaVA Tiny via MoE-Knowledge Distillation
Fangxun Shu, Yue Liao, Lei Zhang et al.
MoE-Gyro: Self-Supervised Over-Range Reconstruction and Denoising for MEMS Gyroscopes
Feiyang Pan, Shenghe Zheng, Chunyan Yin et al.
MoFRR: Mixture of Diffusion Models for Face Retouching Restoration
Jiaxin Liu, Qichao Ying, Zhenxing Qian et al.
MoORE: SVD-based Model MoE-ization for Conflict- and Oblivion-Resistant Multi-Task Adaptation
Shen Yuan, Yin Zheng, Taifeng Wang et al.
MoRE-Brain: Routed Mixture of Experts for Interpretable and Generalizable Cross-Subject fMRI Visual Decoding
YUXIANG WEI, Yanteng Zhang, Xi Xiao et al.
More Experts Than Galaxies: Conditionally-Overlapping Experts with Biologically-Inspired Fixed Routing
Sagi Shaier, Francisco Pereira, Katharina Kann et al.
Multiple Heads are Better than One: Mixture of Modality Knowledge Experts for Entity Representation Learning
Yichi Zhang, Zhuo Chen, Lingbing Guo et al.
Multi-Task Vehicle Routing Solver via Mixture of Specialized Experts under State-Decomposable MDP
Yuxin Pan, Zhiguang Cao, Chengyang GU et al.
NetMoE: Accelerating MoE Training through Dynamic Sample Placement
Xinyi Liu, Yujie Wang, Fangcheng Fu et al.
No Need to Talk: Asynchronous Mixture of Language Models
Anastasiia Filippova, Angelos Katharopoulos, David Grangier et al.
PINN Balls: Scaling Second-Order Methods for PINNs with Domain Decomposition and Adaptive Sampling
Andrea Bonfanti, Ismael Medina, Roman List et al.
Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts
Minh Le, Chau Nguyen, Huy Nguyen et al.
Routing Experts: Learning to Route Dynamic Experts in Existing Multi-modal Large Language Models
Qiong Wu, Zhaoxi Ke, Yiyi Zhou et al.
SAME: Learning Generic Language-Guided Visual Navigation with State-Adaptive Mixture of Experts
Gengze Zhou, Yicong Hong, Zun Wang et al.
Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts
Junmo Kang, Leonid Karlinsky, Hongyin Luo et al.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing
Yingying Zhang, Lixiang Ru, Kang Wu et al.
Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models
Hoang Khoi Nguyen Do, Truc Nguyen, Malik Hassanaly et al.
The Omni-Expert: A Computationally Efficient Approach to Achieve a Mixture of Experts in a Single Expert Model
Sohini Saha, Mezisashe Ojuba, Leslie Collins et al.
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
Xiaoming Shi, Shiyu Wang, Yuqi Nie et al.
Towards Accurate and Efficient 3D Object Detection for Autonomous Driving: A Mixture of Experts Computing System on Edge
Linshen Liu, Boyan Su, Junyue Jiang et al.
Towards Interpretability Without Sacrifice: Faithful Dense Layer Decomposition with Mixture of Decoders
James Oldfield, Shawn Im, Sharon Li et al.
VA-MoE: Variables-Adaptive Mixture of Experts for Incremental Weather Forecasting
Hao Chen, Tao Han, Song Guo et al.
Wasserstein Distances, Neuronal Entanglement, and Sparsity
Shashata Sawmya, Linghao Kong, Ilia Markov et al.
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts
Onur Celik, Aleksandar Taranovic, Gerhard Neumann
A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts
Mohammed Nowaz Rabbani Chowdhury, Meng Wang, Kaoutar El Maghraoui et al.
BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation
Daeun Lee, Jaehong Yoon, Sung Ju Hwang
Boost Your NeRF: A Model-Agnostic Mixture of Experts Framework for High Quality and Efficient Rendering
Francesco Di Sario, Riccardo Renzulli, Marco Grangetto et al.
Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters
Yuhang Zhou, Zhao Zihua, Siyuan Du et al.
Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?
Huy Nguyen, Pedram Akbarian, Nhat Ho
Merging Multi-Task Models via Weight-Ensembling Mixture of Experts
Anke Tang, Li Shen, Yong Luo et al.
Mixture of Efficient Diffusion Experts Through Automatic Interval and Sub-Network Selection
Alireza Ganjdanesh, Yan Kang, Yuchen Liu et al.
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Byung-Kwan Lee, Beomchan Park, Chae Won Kim et al.
MoDE: CLIP Data Experts via Clustering
Jiawei Ma, Po-Yao Huang, Saining Xie et al.
MoEAD: A Parameter-efficient Model for Multi-class Anomaly Detection
Shiyuan Meng, Wenchao Meng, Qihang Zhou et al.
Multi-Task Dense Prediction via Mixture of Low-Rank Experts
Yuqi Yang, Peng-Tao Jiang, Qibin Hou et al.
Norface: Improving Facial Expression Analysis by Identity Normalization
Hanwei Liu, Rudong An, Zhimeng Zhang et al.
On Least Square Estimation in Softmax Gating Mixture of Experts
Huy Nguyen, Nhat Ho, Alessandro Rinaldo