Papers by Aayush Bajaj

2 papers
ChartQAPro: A More Diverse and Challenging Benchmark for Chart Question Answering (2025.findings-acl)

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Challenge: Chart Question Answering systems are limited in their ability to interpret data visually and reason with visual representations.
Approach: They propose a chart-based chart question-answering system that includes 1,341 charts from 99 diverse sources and 1,948 questions in various types.
Outcome: The new benchmark includes 1,341 charts from 99 diverse sources and 1,948 questions in various types.
ChartGemma: Visual Instruction-tuning for Chart Reasoning in the Wild (2025.coling-industry)

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Challenge: Existing methods for chart understanding and reasoning are weakly aligned and rely on underlying data tables.
Approach: They propose a chart-based understanding and reasoning model that is trained on instruction-tuning data generated directly from chart images.
Outcome: The proposed model achieves state-of-the-art results across 5 benchmarks spanning chart summarization, question answering, and fact-checking.

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