{"total":64,"rows":[{"id":"2403.05525","title":"DeepSeek-VL: Towards Real-World Vision-Language Understanding","created":"2024-03-08","cited_by_count":733,"area":null},{"id":"2409.01704","title":"General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model","created":"2024-09-03","cited_by_count":180,"area":null},{"id":"2501.15368","title":"Baichuan-Omni-1.5 Technical Report","created":"2025-01-26","cited_by_count":111,"area":null},{"id":"2504.05506","title":"ChartQAPro: A More Diverse and Challenging Benchmark for Chart Question Answering","created":"2025-04-07","cited_by_count":108,"area":null},{"id":"2407.04172","title":"ChartGemma: Visual Instruction-tuning for Chart Reasoning in the Wild","created":"2024-07-04","cited_by_count":79,"area":null},{"id":"2407.09413","title":"SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers","created":"2024-07-12","cited_by_count":75,"area":null},{"id":"2403.12027","title":"From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Models","created":"2024-03-18","cited_by_count":53,"area":null},{"id":"2404.09987","title":"OneChart: Purify the Chart Structural Extraction via One Auxiliary Token","created":"2024-04-15","cited_by_count":39,"area":null},{"id":"2311.07453","title":"ChartCheck: Explainable Fact-Checking over Real-World Chart Images","created":"2023-11-13","cited_by_count":26,"area":null},{"id":"2404.18144","title":"Generative AI for Visualization: State of the Art and Future Directions","created":"2024-04-28","cited_by_count":23,"area":null},{"id":"2407.11229","title":"Unraveling the Truth: Do VLMs really Understand Charts? A Deep Dive into Consistency and Robustness","created":"2024-07-15","cited_by_count":17,"area":null},{"id":"2409.19242","title":"SciDoc2Diagrammer-MAF: Towards Generation of Scientific Diagrams from Documents guided by Multi-Aspect Feedback Refinement","created":"2024-09-28","cited_by_count":15,"area":null},{"id":"2403.00209","title":"ChartReformer: Natural Language-Driven Chart Image Editing","created":"2024-03-01","cited_by_count":13,"area":null},{"id":"2503.04110","title":"InterChat: Enhancing Generative Visual Analytics using Multimodal Interactions","created":"2025-03-06","cited_by_count":13,"area":null},{"id":"2512.00752","title":"Charts Are Not Images: On the Challenges of Scientific Chart Editing","created":"2025-11-30","cited_by_count":11,"area":null},{"id":"2312.10610","title":"Do LLMs Work on Charts? Designing Few-Shot Prompts for Chart Question Answering and Summarization","created":"2023-12-17","cited_by_count":10,"area":null},{"id":"2501.09349","title":"ChartInsighter: An Approach for Mitigating Hallucination in Time-series Chart Summary Generation with A Benchmark Dataset","created":"2025-01-16","cited_by_count":9,"area":null},{"id":"2511.20648","title":"LocateAnything3D: Vision-Language 3D Detection with Chain-of-Sight","created":"2025-11-25","cited_by_count":8,"area":null},{"id":"2409.18475","title":"Data Analysis in the Era of Generative AI","created":"2024-09-27","cited_by_count":6,"area":null},{"id":"2409.19747","title":"Natural Language Generation for Visualizations: State of the Art, Challenges and Future Directions","created":"2024-09-29","cited_by_count":6,"area":null},{"id":"2411.08397","title":"CLaSP: Learning Concepts for Time-Series Signals from Natural Language Supervision","created":"2024-11-13","cited_by_count":6,"area":null},{"id":"2311.09612","title":"Efficient End-to-End Visual Document Understanding with Rationale Distillation","created":"2023-11-16","cited_by_count":5,"area":null},{"id":"2403.17784","title":"SciCapenter: Supporting Caption Composition for Scientific Figures with Machine-Generated Captions and Ratings","created":"2024-03-26","cited_by_count":5,"area":null},{"id":"2407.21038","title":"Advancing Chart Question Answering with Robust Chart Component Recognition","created":"2024-07-19","cited_by_count":5,"area":null},{"id":"2412.17606","title":"SBS Figures: Pre-training Figure QA from Stage-by-Stage Synthesized Images","created":"2024-12-23","cited_by_count":5,"area":null},{"id":"2505.15046","title":"ChartCards: A Chart-Metadata Generation Framework for Multi-Task Chart Understanding","created":"2025-05-21","cited_by_count":5,"area":null},{"id":"2406.10085","title":"Enhancing Question Answering on Charts Through Effective Pre-training Tasks","created":"2024-06-14","cited_by_count":4,"area":null},{"id":"2503.22693","title":"Bridging Language Models and Financial Analysis","created":"2025-03-14","cited_by_count":4,"area":null},{"id":"2601.12318","title":"Beyond Human Annotation: Recent Advances in Data Generation Methods for Document Intelligence","created":"2026-01-18","cited_by_count":4,"area":null},{"id":"2405.13580","title":"AltChart: Enhancing VLM-based Chart Summarization Through Multi-Pretext Tasks","created":"2024-05-22","cited_by_count":3,"area":null},{"id":"2501.04303","title":"Graph-Based Multimodal Contrastive Learning for Chart Question Answering","created":"2025-01-08","cited_by_count":3,"area":null},{"id":"2503.04065","title":"PP-DocBee: Improving Multimodal Document Understanding Through a Bag of Tricks","created":"2025-03-06","cited_by_count":3,"area":null},{"id":"2510.03341","title":"OpusAnimation: Code-Based Dynamic Chart Generation","created":"2025-10-02","cited_by_count":3,"area":null},{"id":"2603.06958","title":"Chart-RL: Generalized Chart Comprehension via Reinforcement Learning with Verifiable Rewards","created":"2026-03-07","cited_by_count":3,"area":null},{"id":"2408.04852","title":"MSG-Chart: Multimodal Scene Graph for ChartQA","created":"2024-08-09","cited_by_count":2,"area":null},{"id":"2506.06561","title":"LaMP-Cap: Personalized Figure Caption Generation With Multimodal Figure Profiles","created":"2025-06-06","cited_by_count":2,"area":null},{"id":"2507.20046","title":"Infogen: Generating Complex Statistical Infographics from Documents","created":"2025-07-26","cited_by_count":2,"area":null},{"id":"2601.04582","title":"Aligning Text, Code, and Vision: A Multi-Objective Reinforcement Learning Framework for Text-to-Visualization","created":"2026-01-08","cited_by_count":2,"area":null},{"id":"2603.28902","title":"ChartDiff: A Large-Scale Benchmark for Comprehending Pairs of Charts","created":"2026-03-30","cited_by_count":2,"area":null},{"id":"2409.16517","title":"SynChart: Synthesizing Charts from Language Models","created":"2024-09-25","cited_by_count":1,"area":null},{"id":"2509.01959","title":"Structure-aware Contrastive Learning for Diagram Understanding of Multimodal Models","created":"2025-09-02","cited_by_count":1,"area":null},{"id":"2602.07645","title":"From Dead Pixels to Editable Slides: Infographic Reconstruction into Native Google Slides via Vision-Language Region Understanding","created":"2026-02-07","cited_by_count":1,"area":null},{"id":"2602.10138","title":"Multimodal Information Fusion for Chart Understanding: A Survey of MLLMs -- Evolution, Limitations, and Cognitive Enhancement","created":"2026-02-08","cited_by_count":1,"area":null},{"id":"2602.18178","title":"Evaluating Graphical Perception Capabilities of Vision Transformers","created":"2026-02-20","cited_by_count":1,"area":null},{"id":"2604.25220","title":"DATAREEL: Automated Data-Driven Video Story Generation with Animations","created":"2026-04-28","cited_by_count":1,"area":null},{"id":"2605.00800","title":"Generating Statistical Charts with Validation-Driven LLM Workflows","created":"2026-05-01","cited_by_count":1,"area":null},{"id":"2605.26994","title":"ChartAct: A Benchmark for Dynamic Chart Understanding","created":"2026-05-26","cited_by_count":1,"area":null},{"id":"2407.12875","title":"ChatBCG: Can AI Read Your Slide Deck?","created":"2024-07-16","cited_by_count":0,"area":null},{"id":"2508.03725","title":"A Large Language Model Powered Integrated Circuit Footprint Geometry Understanding","created":"2025-07-30","cited_by_count":0,"area":null},{"id":"2512.19173","title":"CycleChart: A Unified Consistency-Based Learning Framework for Bidirectional Chart Understanding and Generation","created":"2025-12-22","cited_by_count":0,"area":null},{"id":"2602.01527","title":"Toward a Machine Bertin: Why Visualization Needs Design Principles for Machine Cognition","created":"2026-02-02","cited_by_count":0,"area":null},{"id":"2602.10023","title":"MEVER: Multi-Modal and Explainable Claim Verification with Graph-based Evidence Retrieval","created":"2026-02-10","cited_by_count":0,"area":null},{"id":"2602.23589","title":"Pseudo Contrastive Learning for Diagram Comprehension in Multimodal Models","created":"2026-02-27","cited_by_count":0,"area":null},{"id":"2603.29211","title":"Xuanwu: Evolving General Multimodal Models into an Industrial-Grade Foundation for Content Ecosystems","created":"2026-03-31","cited_by_count":0,"area":null},{"id":"2604.21344","title":"Beyond Single Plots: A Benchmark for Question Answering on Multi-Charts","created":"2026-04-23","cited_by_count":0,"area":null},{"id":"2604.22938","title":"Large language model-enabled automated data extraction for concrete materials informatics","created":"2026-04-24","cited_by_count":0,"area":null},{"id":"2604.24987","title":"Assessing Y-Axis Influence: Bias in Multimodal Language Models on Chart-to-Table Translation","created":"2026-04-27","cited_by_count":0,"area":null},{"id":"2606.19782","title":"AgentFinVQA: A Deployable Multi-Agent Pipeline for Auditable Financial Chart QA","created":"2026-06-18","cited_by_count":0,"area":null},{"id":"2607.27084","title":"SciFigQual-Bench: A Benchmark for Scientific Figure Quality Assessment with Full-Manuscript Context","created":"2026-07-29","cited_by_count":0,"area":null},{"id":"2608.04374","title":"FinReportBench: Measuring and Improving Institution-Grade Financial Report Generation","created":"2026-08-05","cited_by_count":0,"area":null},{"id":"2608.06062","title":"Bar-JEPA: Extracting Values from Bar Chart with Joint-Embedding Predictive Architecture","created":"2026-08-06","cited_by_count":0,"area":null},{"id":"2609.13745","title":"Inside VLM Chart Reading: Tracing Value Reading from Vertical Bar Charts Across Space and Depth","created":"2026-09-12","cited_by_count":0,"area":null},{"id":"2609.38642","title":"ChartRevise: A Dataset and Evaluation Protocol for Exact Chart Editing via Code","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.14173","title":"Do you \"see\" what I \"see\"? A Multi-panel Visual Question Answer Dataset for Large Language Model Chart Analysis","created":"2026-10-09","cited_by_count":0,"area":null}],"next_cursor":null}