findalexli/SciGraphQA
SciGraphQA: Large-Scale Synthetic Multi-Turn Question-Answering Dataset for Scientific Graphs
This dataset provides a large collection of multi-turn question-answer dialogues specifically about scientific graphs found in Computer Science and Machine Learning papers. It takes in a scientific graph along with its surrounding text context (title, abstract, relevant paragraph) and produces conversational Q&A pairs about the graph's content. Researchers and developers working on AI models for understanding scientific literature would use this to train and evaluate their systems.
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Use this if you are developing or evaluating AI models that need to understand and answer questions about scientific graphs in a conversational manner.
Not ideal if you need a dataset for general image understanding or if your focus is not on multi-turn dialogues derived from academic graph contexts.
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Language
Jupyter Notebook
License
Apache-2.0
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Last pushed
Oct 25, 2024
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