The recent advancements in semantic communication and resource allocation within space-air-ground integrated networks (SAGINs) have shown significant progress, particularly in optimizing bandwidth usage and ensuring reliable, low-latency communication under challenging conditions. Innovations such as hybrid bit-level and generative semantic communication frameworks, enabled by deep reinforcement learning, have demonstrated superior performance in resource conservation and maintaining high data quality. Additionally, the integration of multimodal semantic communication with pilot-guided frameworks has enhanced robustness in dynamic channel states, particularly for audio-visual event localization tasks. The field is also witnessing advancements in generative semantic communication, leveraging large language models to shift from information recovery to regeneration, significantly reducing communication overhead and improving accuracy. Furthermore, diffusion models are being employed for tasks like gesture synthesis and monaural speech enhancement, showcasing their potential in producing semantically rich outputs and enhancing speech quality by leveraging complex-cycle-consistent mechanisms. Overall, the trend is towards more intelligent, adaptive, and generative solutions that address real-world communication challenges with greater efficiency and reliability.