SymbOmni
Agentic omni-model research on symbolic concept learning and continual visual generation.
SymbOmni explores how agentic omni-models can evolve through symbolic concept learning. The project focuses on breaking the continual learning bottleneck in visual generation.
Key points:
- Co-first author project with Jianru Li, Jinxiu Liu, and Tanqing Kuang
- Introduces a symbolic concept box and verbalized backpropagation
- Achieves strong AIGC benchmark performance with more than 40% token reduction
- Revised manuscript is currently under review