Papers › RealCQA: Scientific Chart Question Answering as a Test-bed for First-Order Logic

RealCQA: Scientific Chart Question Answering as a Test-bed for First-Order Logic

3 Aug 2023arXiv:2308.01979archive 2025-07-28

Saleem Ahmed, Bhavin Jawade, Shubham Pandey, Srirangaraj Setlur, Venu Govindaraju

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. Despite efforts to tackle this problem using synthetic charts, solutions are limited by the shortage of annotated real-world data. To fill this gap, we introduce a benchmark and dataset for chart visual QA on real-world charts, offering a systematic analysis of the task and a novel taxonomy for template-based chart question creation. Our contribution includes the introduction of a new answer type, 'list', with both ranked and unranked variations. Our study is conducted on a real-world chart dataset from scientific literature, showcasing higher visual complexity compared to other works. Our focus is on template-based QA and how it can serve as a standard for evaluating the first-order logic capabilities of models. The results of our experiments, conducted on a real-world out-of-distribution dataset, provide a robust evaluation of large-scale pre-trained models and advance the field of chart visual QA and formal logic verification for neural networks in general.

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Code

cse-ai-lab/RealCQA officialmentioned on GitHubpytorch report

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Tasks

Chart Question AnsweringFormal LogicQuestion AnsweringVisual Question Answering

Datasets

Introduced by this paper, per the archive.

RealCQA

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Chart Question Answering RealCQA crct- 11th ep FineTune 1:1 Accuracy 0.239897973990427 #3 of 5 Archive leaderboard report
Chart Question Answering RealCQA vlt5 - 11th ep FineTune 1:1 Accuracy 0.310618012706403 #5 of 5 Archive leaderboard report

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Methods

Focus

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