SOTAVerified

Chart Question Answering

Question Answering task on charts images

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–50 of 50 papers

TitleStatusHype
Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and BeyondCode5
Advancing Multimodal Large Language Models in Chart Question Answering with Visualization-Referenced Instruction TuningCode2
ScreenAI: A Vision-Language Model for UI and Infographics UnderstandingCode2
StructChart: On the Schema, Metric, and Augmentation for Visual Chart UnderstandingCode2
Pix2Struct: Screenshot Parsing as Pretraining for Visual Language UnderstandingCode2
ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical ReasoningCode2
ChartQAPro: A More Diverse and Challenging Benchmark for Chart Question AnsweringCode1
RefChartQA: Grounding Visual Answer on Chart Images through Instruction TuningCode1
VProChart: Answering Chart Question through Visual Perception Alignment Agent and Programmatic Solution ReasoningCode1
SIMPLOT: Enhancing Chart Question Answering by Distilling EssentialsCode1
PaLI-3 Vision Language Models: Smaller, Faster, StrongerCode1
PaLI-X: On Scaling up a Multilingual Vision and Language ModelCode1
UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and ReasoningCode1
Classification-Regression for Chart ComprehensionCode1
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
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
MSG-Chart: Multimodal Scene Graph for ChartQACode0
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
Synthesize Step-by-Step: Tools Templates and LLMs as Data Generators for Reasoning-Based Chart VQA—0
Do LLMs Work on Charts? Designing Few-Shot Prompts for Chart Question Answering and Summarization—0
Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts—0
DCQA: Document-Level Chart Question Answering towards Complex Reasoning and Common-Sense UnderstandingCode0
RealCQA: Scientific Chart Question Answering as a Test-bed for First-Order LogicCode0
Enhanced Chart Understanding in Vision and Language Task via Cross-modal Pre-training on Plot Table Pairs—0
DePlot: One-shot visual language reasoning by plot-to-table translationCode0
MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart DerenderingCode0
Chart Question Answering: State of the Art and Future Directions—0
STL-CQA: Structure-based Transformers with Localization and Encoding for Chart Question Answering—0
PlotQA: Reasoning over Scientific Plots—0
Answering Questions about Data Visualizations using Efficient Bimodal FusionCode0
LEAF-QA: Locate, Encode & Attend for Figure Question Answering—0
DVQA: Understanding Data Visualizations via Question AnsweringCode0
FigureQA: An Annotated Figure Dataset for Visual ReasoningCode0
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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