5 papers
DisCo-Layout: Disentangling and Coordinating Semantic and Physical Refinement in a Multi-Agent Framework for 3D Indoor Layout Synthesis
Jialin Gao, Donghao Zhou, Mingjian Liang +4
3D indoor layout synthesis is crucial for creating virtual environments. Traditional methods struggle with generalization due to fixed datasets. While recent LLM and VLM-based appr…
MagicTailor: Component-Controllable Personalization in Text-to-Image Diffusion Models
Donghao Zhou, Jiancheng Huang, Jinbin Bai +5
Text-to-image diffusion models can generate high-quality images but lack fine-grained control of visual concepts, limiting their creativity. Thus, we introduce component-controllab…
CellVerse: Do Large Language Models Really Understand Cell Biology?
Fan Zhang, Tianyu Liu, Zhihong Zhu +7
Recent studies have demonstrated the feasibility of modeling single-cell data as natural languages and the potential of leveraging powerful large language models (LLMs) for underst…
Point Cloud Understanding via Attention-Driven Contrastive Learning
Yi Wang, Jiaze Wang, Ziyu Guo +5
Recently Transformer-based models have advanced point cloud understanding by leveraging self-attention mechanisms, however, these methods often overlook latent information in less…
MM-Mixing: Multi-Modal Mixing Alignment for 3D Understanding
Jiaze Wang, Yi Wang, Ziyu Guo +5
We introduce MM-Mixing, a multi-modal mixing alignment framework for 3D understanding. MM-Mixing applies mixing-based methods to multi-modal data, preserving and optimizing cross-m…