6 citations · 18 across the 29 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2025
End-to-End Optimization of LLM-Driven Multi-Agent Search Systems via Heterogeneous-Group-Based Reinforcement Learning
Guanzhong Chen, Shaoxiong Yang, Chao Li +3
Large language models (LLMs) are versatile, yet their deployment in complex real-world settings is limited by static knowledge cutoffs and the difficulty of producing controllable…
cs.LG2024
Mixture of Diverse Size Experts
Manxi Sun, Wei Liu, Jian Luan +2
The Sparsely-Activated Mixture-of-Experts (MoE) has gained increasing popularity for scaling up large language models (LLMs) without exploding computational costs. Despite its succ…