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20242026
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cs.CV2025

Diagram-Driven Course Questions Generation

Xinyu Zhang, Lingling Zhang, Yanrui Wu +6

Visual Question Generation (VQG) research focuses predominantly on natural images while neglecting the diagram, which is a critical component in educational materials. To meet the…

cs.CV2025

VProChart: Answering Chart Question through Visual Perception Alignment Agent and Programmatic Solution Reasoning

Muye Huang, Lingling Zhang, Lai Han +3

Charts are widely used for data visualization across various fields, including education, research, and business. Chart Question Answering (CQA) is an emerging task focused on the…

cs.CV2025

ChartSketcher: Reasoning with Multimodal Feedback and Reflection for Chart Understanding

Muye Huang, Lingling Zhang, Jie Ma +6

Charts are high-density visualization carriers for complex data, serving as a crucial medium for information extraction and analysis. Automated chart understanding poses significan…

cs.CV2025

EvoChart: A Benchmark and a Self-Training Approach Towards Real-World Chart Understanding

Muye Huang, Han Lai, Xinyu Zhang +4

Chart understanding enables automated data analysis for humans, which requires models to achieve highly accurate visual comprehension. While existing Visual Language Models (VLMs)…

cs.CV2024

GoT-CQA: Graph-of-Thought Guided Compositional Reasoning for Chart Question Answering

Lingling Zhang, Muye Huang, QianYing Wang +3

Chart Question Answering (CQA) aims at answering questions based on the visual chart content, which plays an important role in chart sumarization, business data analysis, and data…