3 citations · 8 across the 8 of their papers we have counts for
5 papers · 1 filter
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…