SOTAVerified

Chart Question Answering

Question Answering task on charts images

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–25 of 50 papers

TitleStatusHype
ChartReasoner: Code-Driven Modality Bridging for Long-Chain Reasoning in Chart Question Answering—0
ChartMind: A Comprehensive Benchmark for Complex Real-world Multimodal Chart Question Answering—0
ChartCards: A Chart-Metadata Generation Framework for Multi-Task Chart UnderstandingCode0
ChartMuseum: Testing Visual Reasoning Capabilities of Large Vision-Language Models—0
Judging the Judges: Can Large Vision-Language Models Fairly Evaluate Chart Comprehension and Reasoning?Code0
ChartQAPro: A More Diverse and Challenging Benchmark for Chart Question AnsweringCode1
RefChartQA: Grounding Visual Answer on Chart Images through Instruction TuningCode1
DomainCQA: Crafting Expert-Level QA from Domain-Specific Charts—0
Unmasking Deceptive Visuals: Benchmarking Multimodal Large Language Models on Misleading Chart Question Answering—0
ChartCitor: Multi-Agent Framework for Fine-Grained Chart Visual Attribution—0
SBS Figures: Pre-training Figure QA from Stage-by-Stage Synthesized ImagesCode0
RealCQA-V2 : Visual Premise Proving A Manual COT Dataset for Charts—0
ChartKG: A Knowledge-Graph-Based Representation for Chart Images—0
Charting the Future: Using Chart Question-Answering for Scalable Evaluation of LLM-Driven Data Visualizations—0
GoT-CQA: Graph-of-Thought Guided Compositional Reasoning for Chart Question Answering—0
VProChart: Answering Chart Question through Visual Perception Alignment Agent and Programmatic Solution ReasoningCode1
MSG-Chart: Multimodal Scene Graph for ChartQACode0
Advancing Multimodal Large Language Models in Chart Question Answering with Visualization-Referenced Instruction TuningCode2
Advancing Chart Question Answering with Robust Chart Component Recognition—0
Unraveling the Truth: Do VLMs really Understand Charts? A Deep Dive into Consistency and Robustness—0
Are Large Vision Language Models up to the Challenge of Chart Comprehension and Reasoning? An Extensive Investigation into the Capabilities and Limitations of LVLMs—0
ChartInsights: Evaluating Multimodal Large Language Models for Low-Level Chart Question Answering—0
mChartQA: A universal benchmark for multimodal Chart Question Answer based on Vision-Language Alignment and Reasoning—0
Synthesize Step-by-Step: Tools, Templates and LLMs as Data Generators for Reasoning-Based Chart VQA—0
Chart-based Reasoning: Transferring Capabilities from LLMs to VLMs—0
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All datasetsChartQAPlotQARealCQA

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ChartPaLI-5B + PaLM 2-S1:1 Accuracy81.3—Unverified
2Gemini Ultra1:1 Accuracy80.8—Unverified
3DePlot+FlanPaLM+Codex (PoT Self-Consistency)1:1 Accuracy79.3—Unverified
4ChartPaLI-5B1:1 Accuracy77.3—Unverified
5DePlot+Codex (PoT Self-Consistency)1:1 Accuracy76.7—Unverified
6ScreenAI 5B (4.62 B params, w/ OCR)1:1 Accuracy76.7—Unverified
7SMoLA-PaLI-X Specialist Model1:1 Accuracy74.6—Unverified
8SMoLA-PaLI-X Generalist Model1:1 Accuracy73.8—Unverified
9MatCha4096 + LaMenDa1:1 Accuracy72.64—Unverified
10PaLI-X (Single-task FT w/ OCR)1:1 Accuracy72.3—Unverified
#ModelMetricClaimedVerifiedStatus
1MatCha4096 + LaMenDa1:1 Accuracy92.89—Unverified
2MatCha1:1 Accuracy91.5—Unverified
3DePlot+FlanPaLM+Codex (PoT Self-Consistency)1:1 Accuracy66.6—Unverified
4VL-T5-OCR1:1 Accuracy66—Unverified
5CRCT1:1 Accuracy55.7—Unverified
6VisionTapas-OCR1:1 Accuracy53.9—Unverified
#ModelMetricClaimedVerifiedStatus
1vlt5 - 11th ep FineTune1:1 Accuracy0.31—Unverified
2Matcha-chartQA1:1 Accuracy0.26—Unverified
3crct- 11th ep FineTune1:1 Accuracy0.24—Unverified
4vlt5 - baseline1:1 Accuracy0.19—Unverified
5crct - baseline1:1 Accuracy0.18—Unverified