Cover Image

ChartMind: A Comprehensive Benchmark for Complex Real-world Multimodal Chart Question Answering

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wei, Jingxuan, Xu, Nan, Zhu, Junnan, Hao, Yanni, Wu, Gaowei, Yu, Bihui, Wang, Lei
Format:	Preprint
Published:	2025
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ChartReasoner: Code-Driven Modality Bridging for Long-Chain Reasoning in Chart Question Answering
by: Jia, Caijun, et al.
Published: (2025)

TableEval: A Real-World Benchmark for Complex, Multilingual, and Multi-Structured Table Question Answering
by: Zhu, Junnan, et al.
Published: (2025)

Chart-HQA: A Benchmark for Hypothetical Question Answering in Charts
by: Chen, Xiangnan, et al.
Published: (2025)

ChartInsights: Evaluating Multimodal Large Language Models for Low-Level Chart Question Answering
by: Wu, Yifan, et al.
Published: (2024)

ChartQAPro: A More Diverse and Challenging Benchmark for Chart Question Answering
by: Masry, Ahmed, et al.
Published: (2025)

Graph-Based Multimodal Contrastive Learning for Chart Question Answering
by: Dai, Yue, et al.
Published: (2025)

ChartAgent: A Multimodal Agent for Visually Grounded Reasoning in Complex Chart Question Answering
by: Kaur, Rachneet, et al.
Published: (2025)

Chart Question Answering from Real-World Analytical Narratives
by: Hutchinson, Maeve, et al.
Published: (2025)

Advancing Chart Question Answering with Robust Chart Component Recognition
by: Zheng, Hanwen, et al.
Published: (2024)

WikiMixQA: A Multimodal Benchmark for Question Answering over Tables and Charts
by: Foroutan, Negar, et al.
Published: (2025)

Unmasking Deceptive Visuals: Benchmarking Multimodal Large Language Models on Misleading Chart Question Answering
by: Chen, Zixin, et al.
Published: (2025)

POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question Answering
by: Xu, Yichen, et al.
Published: (2025)

InfoChartQA: A Benchmark for Multimodal Question Answering on Infographic Charts
by: Xie, Tianchi, et al.
Published: (2025)

Charting the Future: Using Chart Question-Answering for Scalable Evaluation of LLM-Driven Data Visualizations
by: Ford, James, et al.
Published: (2024)

Beyond Single Plots: A Benchmark for Question Answering on Multi-Charts
by: Efat, Azher Ahmed, et al.
Published: (2026)

LLaVA-NeuMT: Selective Layer-Neuron Modulation for Efficient Multilingual Multimodal Translation
by: Wei, Jingxuan, et al.
Published: (2025)

Chart-to-Experience: Benchmarking Multimodal LLMs for Predicting Experiential Impact of Charts
by: Kim, Seon Gyeom, et al.
Published: (2025)

SIMPLOT: Enhancing Chart Question Answering by Distilling Essentials
by: Kim, Wonjoong, et al.
Published: (2024)

Enhancing Question Answering on Charts Through Effective Pre-training Tasks
by: Gupta, Ashim, et al.
Published: (2024)

CT2C-QA: Multimodal Question Answering over Chinese Text, Table and Chart
by: Zhao, Bowen, et al.
Published: (2024)

MSG-Chart: Multimodal Scene Graph for ChartQA
by: Dai, Yue, et al.
Published: (2024)

ChartInstruct: Instruction Tuning for Chart Comprehension and Reasoning
by: Masry, Ahmed, et al.
Published: (2024)

ChartFI: Benchmarking Faithfulness and Insightfulness of Chart Descriptions from Multimodal Large Language Models
by: Wang, Fen, et al.
Published: (2026)

Evaluating Prompting Strategies for Chart Question Answering with Large Language Models
by: Naikar, Ruthuparna, et al.
Published: (2026)

TRACER: Verifiable Generative Provenance for Multimodal Tool-Using Agents
by: Yu, Bihui, et al.
Published: (2026)

mChartQA: A universal benchmark for multimodal Chart Question Answer based on Vision-Language Alignment and Reasoning
by: Wei, Jingxuan, et al.
Published: (2024)

CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs
by: Wang, Zirui, et al.
Published: (2024)

CHARTOM: A Visual Theory-of-Mind Benchmark for LLMs on Misleading Charts
by: Bharti, Shubham, et al.
Published: (2024)

RealChart2Code: Advancing Chart-to-Code Generation with Real Data and Multi-Task Evaluation
by: Zhang, Jiajun, et al.
Published: (2026)

MultiChartQA: Benchmarking Vision-Language Models on Multi-Chart Problems
by: Zhu, Zifeng, et al.
Published: (2024)

TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
by: Wu, Xianjie, et al.
Published: (2024)

Sentence-Level or Token-Level? A Comprehensive Study on Knowledge Distillation
by: Wei, Jingxuan, et al.
Published: (2024)

ResearchPulse: Building Method-Experiment Chains through Multi-Document Scientific Inference
by: Chen, Qi, et al.
Published: (2025)

Chart-RL: Generalized Chart Comprehension via Reinforcement Learning with Verifiable Rewards
by: Zhang, Xin, et al.
Published: (2026)

Rethinking Text-to-SQL: Dynamic Multi-turn SQL Interaction for Real-world Database Exploration
by: Sun, Linzhuang, et al.
Published: (2025)

ChartCards: A Chart-Metadata Generation Framework for Multi-Task Chart Understanding
by: Wu, Yifan, et al.
Published: (2025)

GenProve: Learning to Generate Text with Fine-Grained Provenance
by: Wei, Jingxuan, et al.
Published: (2026)

ChartAdapter: Large Vision-Language Model for Chart Summarization
by: Xu, Peixin, et al.
Published: (2024)

ChartMark: A Structured Grammar for Chart Annotation
by: Chen, Yiyu, et al.
Published: (2025)

ChartCheck: Explainable Fact-Checking over Real-World Chart Images
by: Akhtar, Mubashara, et al.
Published: (2023)