lightbulb现实痛点ML/AI 模型可视化与可解释分析非技术背景的医疗用户难以选择和理解预测模型。IUI '24VMS: Interactive Visualization to Support the Sensemaking and Selection of Predictive Models
lightbulb现实痛点ML/AI 模型可视化与可解释分析复杂数据文档缺乏直观可视化,用户难以快速理解数据洞察。CHI '25GistVis: Automatic Generation of Word-scale Visualizations from Data-rich Documents
lightbulb现实痛点ML/AI 模型可视化与可解释分析用户在搜索或设计数据可视化时难以快速获得准确的相似性判断。CHI '25Seeing Eye to AI? Applying Deep-Feature-Based Similarity Metrics to Information Visualization
lightbulb现实痛点ML/AI 模型可视化与可解释分析研究者缺乏工具支持从初期构想到具体研究计划的高效转化。CHI '25IdeaSynth: Iterative Research Idea Development Through Evolving and Composing Idea Facets with Literature-Grounded Feedback
lightbulb现实痛点ML/AI 模型可视化与可解释分析交通管理中,检测器数据难以直观地发现异常和模式。IUI '24Improving Interactive Visualization of Large-Scale Traffic Detector Data Using Machine Learning
lightbulb现实痛点ML/AI 模型可视化与可解释分析用户不知道如何快速找到可视化中的关键信息来回答问题。CHI '24SalChartQA: Question-driven Saliency on Information Visualisations
lightbulb现实痛点ML/AI 模型可视化与可解释分析开发者难以高效地测试和优化应用的辅助功能支持。CHI '24AXNav: Replaying Accessibility Tests from Natural Language