Many keywords in a sentence that represents the semantic propensity of the sentence.
These words can exist anywhere in the sentence, which poses a great challenge to …

Task-oriented semantic communications have achieved significant performance gains.
However, the employed deep neural networks in semantic communications have to be …

This paper presents the Generative Adversarial Networks (GANs)-based image semantic
coding, the goal of which is semantic exchange rather than symbol transmission. State-of …

Semantic communications have shown its great potential to improve the transmission
reliability, especially in the low signal-to-noise regime. However, resource allocation for …

Recently, semantic communications are envisioned as a key enabler of future 6G networks.
Back to Shannon's information theory, the goal of communication has long been to …

While semantic communications have shown the potential in the case of single-modal single-
users, its applications to the multi-user scenario remain limited. In this paper, we investigate …

Along with the springing up of the semantics-empowered communication (SemCom)
research, it is now witnessing an unprecedentedly growing interest towards a wide range of …

We introduce two pre-trained retrieval focused multilingual sentence encoding models,
respectively based on the Transformer and CNN model architectures. The models embed …

Although semantic communications have exhibited satisfactory performance on a large
number of tasks, the impact of semantic noise and the robustness of the systems have not …

The last 70 years have witnessed the transition of communication from Shannon's
theoretical concept to current high-efficiency practical systems. Classical communication …