3 papers
cs.CL2025
Router Upcycling: Leveraging Mixture-of-Routers in Mixture-of-Experts Upcycling
Junfeng Ran, Guangxiang Zhao, Yuhan Wu +7
The Mixture-of-Experts (MoE) models have gained significant attention in deep learning due to their dynamic resource allocation and superior performance across diverse tasks. Howev…
cs.CL2025
Chain-of-Thought Matters: Improving Long-Context Language Models with Reasoning Path Supervision
Dawei Zhu, Xiyu Wei, Guangxiang Zhao +7
Recent advances in Large Language Models (LLMs) have highlighted the challenge of handling long-context tasks, where models need to reason over extensive input contexts to aggregat…
cs.CL2025
LongAttn: Selecting Long-context Training Data via Token-level Attention
Longyun Wu, Dawei Zhu, Guangxiang Zhao +5
With the development of large language models (LLMs), there has been an increasing need for significant advancements in handling long contexts. To enhance long-context capabilities…