3 papers
cs.CL2026
Mixture of Heterogeneous Grouped Experts for Language Modeling
Zhicheng Ma, Xiang Liu, Zhaoxiang Liu +5
Large Language Models (LLMs) based on Mixture-of-Experts (MoE) are pivotal in industrial applications for their ability to scale performance efficiently. However, standard MoEs enf…
cs.LG2025
Quantitative Analysis of Performance Drop in DeepSeek Model Quantization
Enbo Zhao, Yi Shen, Shuming Shi +7
Recently, there is a high demand for deploying DeepSeek-R1 and V3 locally, possibly because the official service often suffers from being busy and some organizations have data priv…
cs.LG2025
DAST: Difficulty-Adaptive Slow-Thinking for Large Reasoning Models
Yi Shen, Jian Zhang, Jieyun Huang +7
Recent advancements in slow thinking reasoning models have shown exceptional performance in complex reasoning tasks. However, these models often exhibit overthinking (generating re…