The field of semantic communication is moving towards the development of more robust and efficient systems, focusing on transmitting task-relevant semantic information instead of raw data. Recent work has emphasized the importance of addressing uncertainty and enhancing robustness in semantic communication frameworks. Distributionally robust optimization and cumulative prospect theory are being explored to provide resilience against semantic misinterpretation and channel perturbations. Additionally, cross-modal generative semantic communication and goal-oriented semantic resource allocation are being investigated to improve compression efficiency and support real-time communication. Notable papers in this area include:

• A novel semantic communication framework that employs Wasserstein distributionally robust optimization to provide resilience against semantic misinterpretation and channel perturbations.
• A channel-adaptive cross-modal generative semantic communication framework for point cloud transmission, which leverages generative priors to ensure reliable reconstruction even from noisy or incomplete source point clouds.