Papers with real-world CQA

1 papers
ChartMind: A Comprehensive Benchmark for Complex Real-world Multimodal Chart Question Answering (2025.emnlp-main)

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Challenge: Chart question answering (CQA) is a multimodal task for evaluating the reasoning capabilities of vision-language models.
Approach: They propose a chart question answering benchmark that incorporates multilingual contexts and supports open-domain textual outputs.
Outcome: The proposed framework outperforms the previous three common CQA paradigms: instruction-following, OCR-enhanced, and chain-of-thought.

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