Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model

The rapid development of diffusion models has led to remarkable advancements in the field of image generation. However, well-known models like DALL-E, Stable Diffusion, and Midjourney continue to struggle with challenges such as model bias, limited text rendering capabilities, and an inadequate understanding of cultural nuances, particularly within the Chinese language sphere.

Seedream 2.0, a native Chinese-English bilingual image generation foundation model developed by ByteDance, addresses these challenges. It distinguishes itself through its ability to process text input in both Chinese and English, enabling bilingual image generation and text rendering. The model is based on a powerful data system that facilitates the integration of knowledge and a caption system that balances the accuracy and detail of image descriptions.

A key feature of Seedream 2.0 is the integration of a self-developed bilingual large language model as a text encoder. This allows the model to learn native knowledge directly from extensive datasets and generate images with culturally accurate nuances and aesthetic expressions that can be described in both Chinese and English.

Technical Innovations

For the flexible rendering of text at the character level, Glyph-Aligned ByT5 is utilized, while a scaled ROPE (Rotary Position Embedding) allows for good generalization to untrained resolutions. Multi-phase post-training optimizations, including SFT (Supervised Fine-Tuning) and RLHF (Reinforcement Learning from Human Feedback) iterations, further enhance the overall function of the model.

Extensive experiments have shown that Seedream 2.0 achieves state-of-the-art performance in various aspects, such as prompt adherence, aesthetics, text rendering, and structural correctness. Optimization through multiple RLHF iterations ensures that the model's output is closely aligned with human preferences, as evidenced by an excellent ELO score.

Applications and Future Prospects

Seedream 2.0 can also be easily adapted to an instruction-based image editing model like SeedEdit. This offers powerful editing capabilities that balance adherence to instructions with image consistency. The ability to process both Chinese and English text input opens up new possibilities for content creation that appeals to global audiences.

The development of Seedream 2.0 underscores the growing interest in AI models that consider cultural nuances and linguistic diversity. The integration of advanced techniques like RLHF and the focus on bilingual capabilities position Seedream 2.0 as a promising contribution to the advancement of image generation.

Bibliography: - Gong, Lixue et al. "Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model." arXiv preprint arXiv:2503.07703 (2025). - "Transforming Education with Generative AI." In: Generative AI and Education. Springer, Cham, 2024. - "Generative AI and Education: Ethics, the Curriculum, and New Opportunities." Library of Open Access Publications. - "On the Opportunities and Risks of Foundation Models." arXiv preprint arXiv:2108.07258 (2021). - "Ars Electronica Festival 2024." Ars Electronica.