3 papers
cs.CR2026
SaplingGuard: A Multidimensional-Profile-Aware Multi-Agent Guardrail for Developmentally Safe Adolescent-LLM Interaction
Jing Tan, Yifan Liu, Yi Lin +6
As adolescents increasingly use LLMs in everyday life, ensuring safe and developmentally appropriate responses has become essential. However, existing LLM guardrails primarily targ…
cs.CL2024
Expert-Token Resonance MoE: Bidirectional Routing with Efficiency Affinity-Driven Active Selection
Jing Li, Zhijie Sun, Dachao Lin +5
Mixture-of-Experts (MoE) architectures enable efficient scaling of large language models by activating only a subset of parameters per input. However, existing MoE models suffer fr…
cs.LG2024
LocMoE: A Low-Overhead MoE for Large Language Model Training
Jing Li, Zhijie Sun, Xuan He +6
The Mixtures-of-Experts (MoE) model is a widespread distributed and integrated learning method for large language models (LLM), which is favored due to its ability to sparsify and…