Jingyu Guo — accepted AI-conference papers

2026

DV-World: Benchmarking Data Visualization Agents in Real-World Scenarios

Jinxiang Meng, Shaoping Huang, Fangyu Lei, Jingyu Guo, Haoxiang Liu, Jiahao Su +14

ICML 2026poster

Real-world data visualization (DV) requires native environmental grounding, cross-platform evolution, and proactive intent alignment. Yet, existing benchmarks often suffer from code-sandbox confinement, single-language creation-only tasks, and assumption of perfect intent. To bridge these gaps, we i…

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2026

Learning What Helps: Task-Aligned Context Selection for Vision Tasks

Jingyu Guo, Emir Konuk, Fredrik Strand, Christos Matsoukas, Kevin Smith

CVPR 2026

Humans often resolve visual uncertainty by comparing an image with relevant examples, but ViTs lack the ability to identify which examples would improve their predictions. We present Task-Aligned Context Selection (TACS), a framework that learns to select paired examples which truly improve task per

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