Chart Question Answering
16 papers with code • 3 benchmarks • 8 datasets
Question Answering task on charts images
Benchmarks
These leaderboards are used to track progress in Chart Question Answering
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Libraries
Use these libraries to find Chart Question Answering models and implementations
ChartQA
DVQA
PlotQA
LEAF-QA
RealCQA
Vega-Lite Chart Collection
Most implemented papers
RealCQA: Scientific Chart Question Answering as a Test-bed for First-Order Logic
We present a comprehensive study of chart visual question-answering(QA) task, to address the challenges faced in comprehending and extracting data from chart visualizations within documents.
Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
qwenlm/qwen-vl
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In this work, we introduce the Qwen-VL series, a set of large-scale vision-language models (LVLMs) designed to perceive and understand both texts and images.
StructChart: Perception, Structuring, Reasoning for Visual Chart Understanding
Charts are common in literature across different scientific fields, conveying rich information easily accessible to readers.
PaLI-3 Vision Language Models: Smaller, Faster, Stronger
kyegomez/PALI3
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This paper presents PaLI-3, a smaller, faster, and stronger vision language model (VLM) that compares favorably to similar models that are 10x larger.
DCQA: Document-Level Chart Question Answering towards Complex Reasoning and Common-Sense Understanding
Our DCQA dataset is expected to foster research on understanding visualizations in documents, especially for scenarios that require complex reasoning for charts in the visually-rich document.
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
At the heart of this mixture is a novel screen annotation task in which the model has to identify the type and location of UI elements.
