Saved in:
| Main Authors: | Wan, Cheng, Tao, Runkai, Du, Zheng, Zhao, Yang Katie, Lin, Yingyan Celine |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.01951 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer
by: You, Haoran, et al.
Published: (2023)
by: You, Haoran, et al.
Published: (2023)
MLC-GCN: Multi-Level Generated Connectome Based GCN for AD Analysis
by: Zhu, Wenqi, et al.
Published: (2024)
by: Zhu, Wenqi, et al.
Published: (2024)
MoNTA: Accelerating Mixture-of-Experts Training with Network-Traffc-Aware Parallel Optimization
by: Guo, Jingming, et al.
Published: (2024)
by: Guo, Jingming, et al.
Published: (2024)
PromptGCN: Bridging Subgraph Gaps in Lightweight GCNs
by: Ji, Shengwei, et al.
Published: (2024)
by: Ji, Shengwei, et al.
Published: (2024)
Hybrid GCN-GRU Model for Anomaly Detection in Cryptocurrency Transactions
by: Na, Gyuyeon, et al.
Published: (2025)
by: Na, Gyuyeon, et al.
Published: (2025)
Combining GCN Structural Learning with LLM Chemical Knowledge for Enhanced Virtual Screening
by: Berreziga, Radia, et al.
Published: (2025)
by: Berreziga, Radia, et al.
Published: (2025)
MoR: Mixture Of Representations For Mixed-Precision Training
by: Su, Bor-Yiing, et al.
Published: (2025)
by: Su, Bor-Yiing, et al.
Published: (2025)
MG-Verilog: Multi-grained Dataset Towards Enhanced LLM-assisted Verilog Generation
by: Zhang, Yongan, et al.
Published: (2024)
by: Zhang, Yongan, et al.
Published: (2024)
LUMINA: Laplacian-Unifying Mechanism for Interpretable Neurodevelopmental Analysis via Quad-Stream GCN
by: Cha, Minkyung, et al.
Published: (2026)
by: Cha, Minkyung, et al.
Published: (2026)
Just Propagate: Unifying Matrix Factorization, Network Embedding, and LightGCN for Link Prediction
by: Liu, Haoxin
Published: (2024)
by: Liu, Haoxin
Published: (2024)
Surface EMG Profiling in Parkinson's Disease: Advancing Severity Assessment with GCN-SVM
by: Cieślak, Daniel, et al.
Published: (2025)
by: Cieślak, Daniel, et al.
Published: (2025)
Resilient Temporal GCN for Smart Grid State Estimation Under Topology Inaccuracies
by: Haghshenas, Seyed Hamed, et al.
Published: (2024)
by: Haghshenas, Seyed Hamed, et al.
Published: (2024)
P4GCN: Vertical Federated Social Recommendation with Privacy-Preserving Two-Party Graph Convolution Network
by: Wang, Zheng, et al.
Published: (2024)
by: Wang, Zheng, et al.
Published: (2024)
MergeMix: Optimizing Mid-Training Data Mixtures via Learnable Model Merging
by: Wang, Jiapeng, et al.
Published: (2026)
by: Wang, Jiapeng, et al.
Published: (2026)
WEST GCN-LSTM: Weighted Stacked Spatio-Temporal Graph Neural Networks for Regional Traffic Forecasting
by: Theodoropoulos, Theodoros, et al.
Published: (2024)
by: Theodoropoulos, Theodoros, et al.
Published: (2024)
RGE-GCN: Recursive Gene Elimination with Graph Convolutional Networks for RNA-seq based Early Cancer Detection
by: Shende, Shreyas, et al.
Published: (2025)
by: Shende, Shreyas, et al.
Published: (2025)
Meta-GCN: A Dynamically Weighted Loss Minimization Method for Dealing with the Data Imbalance in Graph Neural Networks
by: Mohammadizadeh, Mahdi, et al.
Published: (2024)
by: Mohammadizadeh, Mahdi, et al.
Published: (2024)
BlockBatch: Multi-Scale Consensus Decoding for Efficient Diffusion Language Model Inference
by: Wu, Xiaoyou, et al.
Published: (2026)
by: Wu, Xiaoyou, et al.
Published: (2026)
Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models
by: Guo, Yongxin, et al.
Published: (2024)
by: Guo, Yongxin, et al.
Published: (2024)
ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
by: You, Haoran, et al.
Published: (2024)
by: You, Haoran, et al.
Published: (2024)
Early-Bird GCNs: Graph-Network Co-Optimization Towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets
by: You, Haoran, et al.
Published: (2021)
by: You, Haoran, et al.
Published: (2021)
Dynamic Expert Quantization for Scalable Mixture-of-Experts Inference
by: Chu, Kexin, et al.
Published: (2025)
by: Chu, Kexin, et al.
Published: (2025)
MA2GCN: Multi Adjacency relationship Attention Graph Convolutional Networks for Traffic Prediction using Trajectory data
by: Sun, Zhengke, et al.
Published: (2024)
by: Sun, Zhengke, et al.
Published: (2024)
Speculating Experts Accelerates Inference for Mixture-of-Experts
by: Madan, Vivan, et al.
Published: (2026)
by: Madan, Vivan, et al.
Published: (2026)
MixtureKit: A General Framework for Composing, Training, and Visualizing Mixture-of-Experts Models
by: Chamma, Ahmad, et al.
Published: (2025)
by: Chamma, Ahmad, et al.
Published: (2025)
KAN-GCN: Combining Kolmogorov-Arnold Network with Graph Convolution Network for an Accurate Ice Sheet Emulator
by: Liu, Zesheng, et al.
Published: (2025)
by: Liu, Zesheng, et al.
Published: (2025)
When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models
by: You, Haoran, et al.
Published: (2024)
by: You, Haoran, et al.
Published: (2024)
Elastic MoE: Unlocking the Inference-Time Scalability of Mixture-of-Experts
by: Gu, Naibin, et al.
Published: (2025)
by: Gu, Naibin, et al.
Published: (2025)
Score-of-Mixture Training: Training One-Step Generative Models Made Simple via Score Estimation of Mixture Distributions
by: Jayashankar, Tejas, et al.
Published: (2025)
by: Jayashankar, Tejas, et al.
Published: (2025)
SMILE: Zero-Shot Sparse Mixture of Low-Rank Experts Construction From Pre-Trained Foundation Models
by: Tang, Anke, et al.
Published: (2024)
by: Tang, Anke, et al.
Published: (2024)
ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks
by: You, Haoran, et al.
Published: (2022)
by: You, Haoran, et al.
Published: (2022)
MoBiE: Efficient Inference of Mixture of Binary Experts under Post-Training Quantization
by: Zhao, Zhixiong, et al.
Published: (2026)
by: Zhao, Zhixiong, et al.
Published: (2026)
Least-Loaded Expert Parallelism: Load Balancing An Imbalanced Mixture-of-Experts
by: Nguyen, Xuan-Phi, et al.
Published: (2026)
by: Nguyen, Xuan-Phi, et al.
Published: (2026)
BigMac: A Communication-Efficient Mixture-of-Experts Model Structure for Fast Training and Inference
by: Jin, Zewen, et al.
Published: (2025)
by: Jin, Zewen, et al.
Published: (2025)
Accelerating Mixture-of-Expert Inference with Adaptive Expert Split Mechanism
by: Yan, Jiaming, et al.
Published: (2025)
by: Yan, Jiaming, et al.
Published: (2025)
N-vium: Mixture-of-Exits Transformer for Accelerated Exact Generation
by: Lorenc, Aleksander, et al.
Published: (2026)
by: Lorenc, Aleksander, et al.
Published: (2026)
Mixture of Experts in a Mixture of RL settings
by: Willi, Timon, et al.
Published: (2024)
by: Willi, Timon, et al.
Published: (2024)
MoE-DisCo:Low Economy Cost Training Mixture-of-Experts Models
by: Ye, Xin, et al.
Published: (2026)
by: Ye, Xin, et al.
Published: (2026)
An Adaptive Placement and Parallelism Framework for Accelerating RLHF Training
by: Xiao, Youshao, et al.
Published: (2023)
by: Xiao, Youshao, et al.
Published: (2023)
Dense Backpropagation Improves Training for Sparse Mixture-of-Experts
by: Panda, Ashwinee, et al.
Published: (2025)
by: Panda, Ashwinee, et al.
Published: (2025)
Similar Items
-
ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer
by: You, Haoran, et al.
Published: (2023) -
MLC-GCN: Multi-Level Generated Connectome Based GCN for AD Analysis
by: Zhu, Wenqi, et al.
Published: (2024) -
MoNTA: Accelerating Mixture-of-Experts Training with Network-Traffc-Aware Parallel Optimization
by: Guo, Jingming, et al.
Published: (2024) -
PromptGCN: Bridging Subgraph Gaps in Lightweight GCNs
by: Ji, Shengwei, et al.
Published: (2024) -
Hybrid GCN-GRU Model for Anomaly Detection in Cryptocurrency Transactions
by: Na, Gyuyeon, et al.
Published: (2025)