SciEGQA: A Dataset for Scientific Evidence-Grounded Question Answering and Reasoning

1. 1Identify complex multimodal structures in scientific documents
2. 2Annotate evidence regions that support the answer
3. 3Evaluate models using the SciEGQA dataset to improve interpretability and reliability
4. 4Apply the dataset to real-world applications such as Document Visual Question Answering

Data scientists and AI researchers on a team benefit from this dataset as it provides a comprehensive benchmark for evaluating models, while product managers can utilize it to improve the reliability of their question answering systems

💡 The SciEGQA dataset provides a benchmark for evaluating models on scientific evidence-grounded question answering and reasoning, improving interpretability and reliability

🚀 SciEGQA dataset for scientific evidence-grounded QA and reasoning! 📚