5 papers
StateScribe: Towards Accessible Change Awareness Across Real-World Revisits
Ruei-Che Chang, Xirui Jiang, Rosiana Natalie +6
Real-world environments evolve continuously, yet blind and low-vision (BLV) individuals often have limited access to understanding how they change over time. Unexpected or relocate…
Enhancing Large Language Models (LLMs) for Telecom using Dynamic Knowledge Graphs and Explainable Retrieval-Augmented Generation
Dun Yuan, Hao Zhou, Xue Liu +4
Large language models (LLMs) have shown strong potential across a variety of tasks, but their application in the telecom field remains challenging due to domain complexity, evolvin…
Hierarchical Debate-Based Large Language Model (LLM) for Complex Task Planning of 6G Network Management
Yuyan Lin, Hao Zhou, Chengming Hu +5
6G networks have become increasingly complicated due to novel network architecture and newly emerging signal processing and transmission techniques, leading to significant burdens…
Enhancing Large Language Models (LLMs) for Telecommunications using Knowledge Graphs and Retrieval-Augmented Generation
Dun Yuan, Hao Zhou, Di Wu +5
Large language models (LLMs) have made significant progress in general-purpose natural language processing tasks. However, LLMs are still facing challenges when applied to domain-s…
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain
Ye Yuan, Haolun Wu, Hao Zhou +5
Knowledge understanding is a foundational part of envisioned 6G networks to advance network intelligence and AI-native network architectures. In this paradigm, information extracti…