1 citations · 1 across the 3 of their papers we have counts for
4 papers
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…
From Intent to Evidence: A Categorical Approach for Structural Evaluation of Deep Research Agents
Shuoling Liu, Zhiquan Tan, Kun Yi +6
Deep Research Agents (DRAs) aim to answer complex questions by searching the web, checking evidence, and synthesizing conclusions across heterogeneous sources. We introduce a categ…
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…
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…