3 citations · 8 across the 8 of their papers we have counts for
8 papers
OmniDiT: Extending Diffusion Transformer to Omni-VTON Framework
Weixuan Zeng, Pengcheng Wei, Huaiqing Wang +8
Despite the rapid advancement of Virtual Try-On (VTON) and Try-Off (VTOFF) technologies, existing VTON methods face challenges with fine-grained detail preservation, generalization…
AKRMap: Adaptive Kernel Regression for Trustworthy Visualization of Cross-Modal Embeddings
Yilin Ye, Junchao Huang, Xingchen Zeng +2
Cross-modal embeddings form the foundation for multi-modal models. However, visualization methods for interpreting cross-modal embeddings have been primarily confined to traditiona…
SketchFlex: Facilitating Spatial-Semantic Coherence in Text-to-Image Generation with Region-Based Sketches
Haichuan Lin, Yilin Ye, Jiazhi Xia +1
Text-to-image models can generate visually appealing images from text descriptions. Efforts have been devoted to improving model controls with prompt tuning and spatial conditionin…
Advancing Multimodal Large Language Models in Chart Question Answering with Visualization-Referenced Instruction Tuning
Xingchen Zeng, Haichuan Lin, Yilin Ye +1
Emerging multimodal large language models (MLLMs) exhibit great potential for chart question answering (CQA). Recent efforts primarily focus on scaling up training datasets (i.e.,…
ModalChorus: Visual Probing and Alignment of Multi-modal Embeddings via Modal Fusion Map
Yilin Ye, Shishi Xiao, Xingchen Zeng +1
Multi-modal embeddings form the foundation for vision-language models, such as CLIP embeddings, the most widely used text-image embeddings. However, these embeddings are vulnerable…
VisTR: Visualizations as Representations for Time-series Table Reasoning
Jianing Hao, Zhuowen Liang, Chunting Li +3
Time-series table reasoning interprets temporal patterns and relationships in data to answer user queries. Despite recent advancements leveraging large language models (LLMs), exis…
Generative AI for Visualization: State of the Art and Future Directions
Yilin Ye, Jianing Hao, Yihan Hou +4
Generative AI (GenAI) has witnessed remarkable progress in recent years and demonstrated impressive performance in various generation tasks in different domains such as computer vi…
IntentTuner: An Interactive Framework for Integrating Human Intents in Fine-tuning Text-to-Image Generative Models
Xingchen Zeng, Ziyao Gao, Yilin Ye +1
Fine-tuning facilitates the adaptation of text-to-image generative models to novel concepts (e.g., styles and portraits), empowering users to forge creatively customized content. R…