3 citations · 12 across the 15 of their papers we have counts for
15 papers
LandSAR: Visceralizing Landslide Data for Enhanced Situational Awareness in Immersive Analytics
Wong Kam-Kwai, Yi-Lin Ye, Wai Tong +7
Landslides pose a significant threat to public safety, but their dynamic processes are difficult to analyze from post-event observation alone. Computational simulation is therefore…
C2Views: Knowledge-based Colormap Design for Multiple-View Consistency
Yihan Hou, Yilin Ye, Liangwei Wang +2
Multiple-view (MV) visualization provides a comprehensive and integrated perspective on complex data, establishing itself as an effective method for visual communication and explor…
Interactive Graph Visualization and TeamingRecommendation in an Interdisciplinary Project'sTalent Knowledge Graph
Jiawei Xu, Juichien Chen, Yilin Ye +5
Interactive visualization of large scholarly knowledge graphs combined with LLM reasoning shows promise butremains under-explored. We address this gap by developing an interactive…
MedBookVQA: A Systematic and Comprehensive Medical Benchmark Derived from Open-Access Book
Sau Lai Yip, Sunan He, Yuxiang Nie +4
The accelerating development of general medical artificial intelligence (GMAI), powered by multimodal large language models (MLLMs), offers transformative potential for addressing…
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…
InfoChartQA: A Benchmark for Multimodal Question Answering on Infographic Charts
Tianchi Xie, Minzhi Lin, Mengchen Liu +3
Understanding infographic charts with design-driven visual elements (e.g., pictograms, icons) requires both visual recognition and reasoning, posing challenges for multimodal large…
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…
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…
The Contemporary Art of Image Search: Iterative User Intent Expansion via Vision-Language Model
Yilin Ye, Qian Zhu, Shishi Xiao +2
Image search is an essential and user-friendly method to explore vast galleries of digital images. However, existing image search methods heavily rely on proximity measurements lik…
TimeTuner: Diagnosing Time Representations for Time-Series Forecasting with Counterfactual Explanations
Jianing Hao, Qing Shi, Yilin Ye +1
Deep learning (DL) approaches are being increasingly used for time-series forecasting, with many efforts devoted to designing complex DL models. Recent studies have shown that the…
Let the Chart Spark: Embedding Semantic Context into Chart with Text-to-Image Generative Model
Shishi Xiao, Suizi Huang, Yue Lin +2
Pictorial visualization seamlessly integrates data and semantic context into visual representation, conveying complex information in a manner that is both engaging and informative.…
Everyone Can Be Picasso? A Computational Framework into the Myth of Human versus AI Painting
Yilin Ye, Rong Huang, Kang Zhang +1
The recent advances of AI technology, particularly in AI-Generated Content (AIGC), have enabled everyone to easily generate beautiful paintings with simple text description. With t…