3 citations · 5 across the 4 of their papers we have counts for
4 papers
EvoRubric: Self-Evolving Rubric-Driven RL for Open-Ended Generation
Xin Guan, Xiaomeng Hu, Shen Huang +6
Reinforcement Learning (RL) has advanced Large Language Models (LLMs) in verifiable domains, while open-ended generation remains challenging due to the absence of definitive reward…
WirelessAgent: Large Language Model Agents for Intelligent Wireless Networks
Jingwen Tong, Wei Guo, Jiawei Shao +4
The rapid evolution of wireless networks presents unprecedented challenges in managing complex and dynamic systems. Existing methods are increasingly facing fundamental limitations…
WirelessAgent: Large Language Model Agents for Intelligent Wireless Networks
Jingwen Tong, Jiawei Shao, Qiong Wu +4
Wireless networks are increasingly facing challenges due to their expanding scale and complexity. These challenges underscore the need for advanced AI-driven strategies, particular…
WirelessLLM: Empowering Large Language Models Towards Wireless Intelligence
Jiawei Shao, Jingwen Tong, Qiong Wu +4
The rapid evolution of wireless technologies and the growing complexity of network infrastructures necessitate a paradigm shift in how communication networks are designed, configur…