Yulong Ao

Beijing Academy of Artificial Intelligence

Papers

1

Total Citations

3

H-Index

1

About

Yulong Ao is a leading researcher in artificial intelligence, with a primary focus on multimodal learning and large-scale generative models. His most influential work centers on advancing next-token prediction frameworks to unify learning across text, images, and video—a fundamental challenge in AI. In his landmark 2026 paper, "Multimodal learning with next-token prediction for large multimodal models," Ao proposed a novel algorithm that extends the success of large language models into multimodal domains, enabling seamless generation and understanding across diverse data types. This contribution has quickly garnered attention, earning 3 citations in its early stages, and is poised to shape the next generation of foundation models. Ao’s research bridges critical gaps between language and vision, offering a scalable, unified approach to multimodal intelligence. His work is particularly notable for its potential to democratize AI capabilities, making sophisticated multimodal interaction more accessible. As a rising figure in the field, Ao’s innovative algorithms are already influencing both academic research and practical applications in generative AI.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Multimodal learning with next-token prediction for large multimodal models
3 citations · 2026
📈 Most Prolific Year: 2026 (1 Papers)
🤝 Key Collaborators: 24
🏛 Institutions: Beijing Academy of Artificial Intelligence

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago