IEEE

Leveraging Large Language Models for Intelligent Control of 6G Integrated TN-NTN With IoT Service

Abstract: With the advent of sixth generation (6G) Internet of Things (IoT), integrated terrestrial network (TN) and non-terrestrial network (NTN) will play a vital role in enabling new applications ...

New agentic memory framework uses 118K tokens per query. LangMem burns through 3.26M.

NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — using step-by-step reasoning.
IEEE

Leveraging Large Language Models for Integrated Satellite-Aerial-Terrestrial Networks: Recent Advances and Future Directions

Abstract: Integrated satellite, aerial, and terrestrial networks (ISATNs) represent a sophisticated convergence of diverse communication technologies to ensure seamless connectivity across different ...