Papers by Mehrad Shahmohammadi

2 papers
ChartInstruct: Instruction Tuning for Chart Comprehension and Reasoning (2024.findings-acl)

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Challenge: Charts provide visual representations of data and are used for analyzing information, addressing queries, and conveying insights to others.
Approach: They propose a chart-specific vision-language Instruction-following dataset with 191K instructions and a pipeline model that extracts chart data tables and inputs them into a LLM.
Outcome: The proposed model can solve a wide range of chart-related tasks, achieving state-of-the-art results on four tasks.
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.

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