AGI-Driven Generative Semantic Communications: Principles and Practices
원문 초록
Semantic communications leverage artificial intelligence (AI) technologies to extract semantic information for efficient data delivery, thereby significantly reducing communication cost. With the evolution towards artificial general intelligence (AGI), the increasing demands for AGI services pose new challenges to semantic communications. In this context, an AGI application is typically defined on a general-sense task, covering a broad, even unforeseen, set of objectives, as well as driven by the need for a human-friendly interface in forms (e.g., videos, images, or text) easily understood by human users.In response, we introduce an AGI-driven communication paradigm for supporting AGI applications, called generative semantic communication (GSC). We first describe the basic concept of GSC and its difference from existing semantic communications, and then introduce a general framework of GSC based on advanced AI technologies including foundation models and generative models. Two case studies are presented to verify the advantages of GSC. Finally, open challenges and new research directions are discussed to stimulate this line of research and pave the way for practical applications.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Adaptive Semantic Token Communication for Transformer-based Edge Inference
SCU: An Efficient Machine Unlearning Scheme for Deep Learning Enabled Semantic Communications
SpikACom: A Neuromorphic Computing Framework for Green Communications
GenSC-6G: A Prototype Testbed for Integrated Generative AI, Quantum, and Semantic Communication
Large Model Empowered Streaming Speech Semantic Communications
Semantic-Aware Resource Management for C-V2X Platooning via Multi-Agent Reinforcement Learning
토론
이 논문과 연결된 포럼 글이 아직 없습니다.