Xuanwu: Evolving General Multimodal Models into an Industrial-Grade Foundation for Content Ecosystems
In recent years, multimodal large models have continued to improve on general benchmarks. However, in real-world content moderation and adversarial settings, mainstream models still suffer from degraded generalization and catastrophic forgetting because of limited fine-grained visual perception and insufficient modeling of long-tail noise. In this paper, we present Xuanwu VL-2B as a case study of how general multimodal models can be developed into an industrial-grade foundation model for content ecosystems. The model adopts a compact InternViT-300M + MLP + Qwen3 1.7B architecture, balancing fine-grained visual perception, language-semantic alignment, and deployment cost within an approxim...
| Authors | Zhiqian Zhang, Xu Zhao, Xiaoqing Xu et al. |
|---|---|
| Primary category | cs.AI |
| Published | 31 March 2026 |
| Last updated at source | 31 March 2026 |
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