3 papers
cs.CL2025
Infinity Instruct: Scaling Instruction Selection and Synthesis to Enhance Language Models
Jijie Li, Li Du, Hanyu Zhao +5
Large Language Models (LLMs) demonstrate strong performance in real-world applications, yet existing open-source instruction datasets often concentrate on narrow domains, such as m…
cs.RO2025
RoboOS: A Hierarchical Embodied Framework for Cross-Embodiment and Multi-Agent Collaboration
Huajie Tan, Xiaoshuai Hao, Cheng Chi +13
The dawn of embodied intelligence has ushered in an unprecedented imperative for resilient, cognition-enabled multi-agent collaboration across next-generation ecosystems, revolutio…
cs.CL2024
AquilaMoE: Efficient Training for MoE Models with Scale-Up and Scale-Out Strategies
Bo-Wen Zhang, Liangdong Wang, Ye Yuan +24
In recent years, with the rapid application of large language models across various fields, the scale of these models has gradually increased, and the resources required for their…