3 papers
cs.DC2026
GRACE-MoE: Grouping and Replication with Locality-Aware Routing for Efficient Distributed MoE Inference
Yu Han, Lehan Pan, Jie Peng +4
Sparse Mixture of Experts (SMoE) enables scalable parameter growth in large language models (LLMs) by selectively activating a subset of experts, and its large parameter count nece…
cs.CL2026
Making Every Verified Token Count: Adaptive Verification for MoE Speculative Decoding
Lehan Pan, Ziyang Tao, Ruoyu Pang +3
Tree-based speculative decoding accelerates autoregressive generation by verifying multiple draft candidates in parallel, but this advantage weakens for sparse Mixture-of-Experts (…
cs.CV2025
Self-Supervised Pre-training with Combined Datasets for 3D Perception in Autonomous Driving
Shumin Wang, Zhuoran Yang, Lidian Wang +7
The significant achievements of pre-trained models leveraging large volumes of data in the field of NLP and 2D vision inspire us to explore the potential of extensive data pre-trai…