1 citations · 1 across the 5 of their papers we have counts for
5 papers
SpikingBrain2.0: Brain-Inspired Foundation Models for Efficient Long-Context and Cross-Platform Inference
Yuqi Pan, Jinghao Zhuang, Yupeng Feng +16
Scaling context length is reshaping large-model development, yet full-attention Transformers suffer from prohibitive computation and inference bottlenecks at long sequences. A key…
Adaptive Hopfield Network: Rethinking Similarities in Associative Memory
Shurong Wang, Yuqi Pan, Zhuoyang Shen +3
Associative memory models are content-addressable memory systems fundamental to biological intelligence and are notable for their high interpretability. However, existing models ev…
MoE: Optimizing Collaborative Inference for Edge Large Language Models
Lyudong Jin, Yanning Zhang, Yanhan Li +4
Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing tasks. Exploiting the heterogeneous capabilities of edge L…
DynFrs: An Efficient Framework for Machine Unlearning in Random Forest
Shurong Wang, Zhuoyang Shen, Xinbao Qiao +2
Random Forests are widely recognized for establishing efficacy in classification and regression tasks, standing out in various domains such as medical diagnosis, finance, and perso…
Harmonizing Human Insights and AI Precision: Hand in Hand for Advancing Knowledge Graph Task
Shurong Wang, Yufei Zhang, Xuliang Huang +1
Knowledge graph embedding (KGE) has caught significant interest for its effectiveness in knowledge graph completion (KGC), specifically link prediction (LP), with recent KGE models…