The field of video generation is rapidly advancing with a focus on improving the quality, efficiency, and interactivity of generated videos. Recent developments have led to the creation of more realistic and expressive videos, with a greater emphasis on integrating audio and visual elements. One of the key trends is the use of diffusion models, which have shown promising results in generating high-quality videos. Another area of focus is on improving the efficiency of video generation models, allowing for real-time and interactive applications. Noteworthy papers in this area include: Seedance 1.0, which introduces a high-performance video foundation generation model that balances prompt following, motion plausibility, and visual quality. M4V, which proposes a Multi-Modal Mamba framework for text-to-video generation, reducing computational costs while producing high-quality videos.