2 papers
cs.CL2025
FLAME-MoE: A Transparent End-to-End Research Platform for Mixture-of-Experts Language Models
Hao Kang, Zichun Yu, Chenyan Xiong
Recent large language models such as Gemini-1.5, DeepSeek-V3, and Llama-4 increasingly adopt Mixture-of-Experts (MoE) architectures, which offer strong efficiency-performance trade…
cs.IR2024
Interpret and Control Dense Retrieval with Sparse Latent Features
Hao Kang, Tevin Wang, Chenyan Xiong
Dense embeddings deliver strong retrieval performance but often lack interpretability and controllability. This paper introduces a novel approach using sparse autoencoders (SAE) to…