From Semantic to Token Communication: The Next Paradigm for Large-Model-Driven 6G Intelligent Connectivity

@misc{ma2026from,
  title = {{From Semantic to Token Communication: The Next Paradigm for Large-Model-Driven 6G Intelligent Connectivity}},
  author = {Yu Ma and Zhen Gao and Li Qiao and Xiaoyuan Zhang and Mahdi Boloursaz Mashhadi and Yin Xu and Wenjun Xu and Xiaodong Xu and Kaibin Huang and Jiangzhou Wang and Rahim Tafazolli and Sheng Chen and Tony Q. S. Quek and Ping Zhang},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.10714},
  eprint = {2609.10714},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.10714},
}

TY  - UNPB
TI  - From Semantic to Token Communication: The Next Paradigm for Large-Model-Driven 6G Intelligent Connectivity
AU  - Yu Ma
AU  - Zhen Gao
AU  - Li Qiao
AU  - Xiaoyuan Zhang
AU  - Mahdi Boloursaz Mashhadi
AU  - Yin Xu
AU  - Wenjun Xu
AU  - Xiaodong Xu
AU  - Kaibin Huang
AU  - Jiangzhou Wang
AU  - Rahim Tafazolli
AU  - Sheng Chen
AU  - Tony Q. S. Quek
AU  - Ping Zhang
PY  - 2026
DA  - 2026/09/09
PB  - arXiv
DO  - 10.48550/arxiv.2609.10714
UR  - https://arxiv.org/abs/2609.10714
AB  - The ambitious requirements of sixth-generation (6G) networks are driving communication systems from reliable bit delivery toward meaning-aware and task-oriented connectivity. Large models (LMs), with strong multimodal understanding and generation capabilities, have accelerated this shift and made semantic communication (SemCom) increasingly practical. Yet current LM-driven SemCom remains fragmented: semantic representations are typically tied to specific modalities, models, or tasks. While the bit provides a universal unit for digital transport, there is still no analogous unit for representing and processing semantics, which limits interoperability, theoretical unification, and scalable system design. We argue that tokens provide a natural candidate for this missing abstraction. Two trends support this: unified multimodal LMs now encode text, images, audio, video, and robot actions in one token space, while distributed LM inference already generates substantial token-level traffic through expert routing, cache transfer, and speculative decoding. Token communication (TokenCom) emerges by unifying these trends, using the LM's native processing unit as a communication abstraction above the bit level and enabling importance assignment, error handling, and resource allocation directly at token granularity. This survey traces the evolution from LM-driven SemCom to TokenCom. We review three major directions of LM-driven SemCom: source-centric semantic coding, channel semantics for physical-layer tasks, and collaborative edge-device intelligence. We then examine the token abstraction, the transmission techniques it requires, and two emerging paradigms, namely TokenCom for LM services and for embodied and agentic intelligence. Finally, we identify open challenges toward unified, scalable, and AI-native 6G communication systems.
ER  -