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cs.CV2026
OP-CAD: On-Policy Clean-Audio Distillation for Robust Audio-Visual Reasoning
Xingming Shui, Dapeng Chen, Bowei Liu +5
Omni-modal large language models deployed in real-world environments encounter external noise that can interfere with their perception and understanding of multimodal inputs. We st…
cs.CV2024★ 1 cited
SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation
Yuying Ge, Sijie Zhao, Jinguo Zhu +6
The rapid evolution of multimodal foundation model has demonstrated significant progresses in vision-language understanding and generation, e.g., our previous work SEED-LLaMA. Howe…
cs.CV2023
ViT-Lens: Initiating Omni-Modal Exploration through 3D Insights
Weixian Lei, Yixiao Ge, Jianfeng Zhang +4
Though the success of CLIP-based training recipes in vision-language models, their scalability to more modalities (e.g., 3D, audio, etc.) is limited to large-scale data, which is e…