# DataVista: Diagnosing Multimodal LLMs on Data Video Understanding

arXiv: https://arxiv.org/abs/2610.11993 · HTML: https://mlsanity.com/paper/2610.11993/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Chart understanding and anomaly detection, one of 16 directions in Multimodal LLMs / vision-language models.
- Builds on 29 of its 86 references that are in the map.
- First posted on arXiv 8 Oct 2026.

## Placed in

- Multimodal LLMs / vision-language models / [Chart understanding and anomaly detection](https://mlsanity.com/mllm/chart-understanding-and-anomaly-detection/)

## Builds on (most cited first, 29 of 29)

- [Qwen2.5-VL Technical Report](https://mlsanity.com/paper/2502.13923/) (2025)
- [Qwen3-VL Technical Report](https://mlsanity.com/paper/2511.21631/) (2025)
- [InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models](https://mlsanity.com/paper/2504.10479/) (2025)
- [InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency](https://mlsanity.com/paper/2508.18265/) (2025)
- [LVBench: An Extreme Long Video Understanding Benchmark](https://mlsanity.com/paper/2406.08035/) (2024)
- [Video-MME-v2: Towards the Next Stage in Benchmarks for Comprehensive Video Understanding](https://mlsanity.com/paper/2604.05015/) (2026)
- [A Survey of Data Agents: Emerging Paradigm or Overstated Hype?](https://mlsanity.com/paper/2510.23587/) (2025)
- [HAIChart: Human and AI Paired Visualization System](https://mlsanity.com/paper/2406.11033/) (2024)
- [Neptune: The Long Orbit to Benchmarking Long Video Understanding](https://mlsanity.com/paper/2412.09582/) (2024)
- [nvBench 2.0: Resolving Ambiguity in Text-to-Visualization through Stepwise Reasoning](https://mlsanity.com/paper/2503.12880/) (2025)
- [IGenBench: Benchmarking the Reliability of Text-to-Infographic Generation](https://mlsanity.com/paper/2601.04498/) (2026)
- [AskChart: Universal Chart Understanding through Textual Enhancement](https://mlsanity.com/paper/2412.19146/) (2024)
- [You Don't Know Until You Click:Automated GUI Testing for Production-Ready Software Evaluation](https://mlsanity.com/paper/2508.14104/) (2025)
- [DeepVIS: Bridging Natural Language and Data Visualization Through Step-wise Reasoning](https://mlsanity.com/paper/2508.01700/) (2025)
- [Data Playwright: Authoring Data Videos with Annotated Narration](https://mlsanity.com/paper/2410.03093/) (2024)
- [HumanVideo-MME: Benchmarking MLLMs for Human-Centric Video Understanding](https://mlsanity.com/paper/2507.04909/) (2025)
- [ChartCards: A Chart-Metadata Generation Framework for Multi-Task Chart Understanding](https://mlsanity.com/paper/2505.15046/) (2025)
- [Demonstrating chart-plot: Closing the Last Mile of Academic Chart Generation](https://mlsanity.com/paper/2606.09174/) (2026)
- [sketch-plot: Progressive Editing for Text-to-Image Academic Figures](https://mlsanity.com/paper/2606.09171/) (2026)
- [DataSpace: Benchmarking Data Agents for Verifiable Analytics over Heterogeneous Workspaces](https://mlsanity.com/paper/2608.03451/) (2026)
- [VisTR: Visualizations as Representations for Time-series Table Reasoning](https://mlsanity.com/paper/2406.03753/) (2024)
- [How Does Empirical Research Facilitate Creation Tool Design? A Data Video Perspective](https://mlsanity.com/paper/2507.15244/) (2025)
- [TableTale: Reviving the Narrative Interplay Between Data Tables and Text in Scientific Papers](https://mlsanity.com/paper/2602.22908/) (2026)
- [ViviDoc: Generating Interactive Documents through Human-Agent Collaboration](https://mlsanity.com/paper/2603.27991/) (2026)
- [ChartDiff: A Large-Scale Benchmark for Comprehending Pairs of Charts](https://mlsanity.com/paper/2603.28902/) (2026)
- [Boosting Text-to-Chart Retrieval through Training with Synthesized Semantic Insights](https://mlsanity.com/paper/2505.10043/) (2025)
- [VideoAesBench: Benchmarking the Video Aesthetics Perception Capabilities of Large Multimodal Models](https://mlsanity.com/paper/2601.21915/) (2026)
- [Exploring Agentic Visual Analytics: A Co-Evolutionary Framework of Roles and Workflows](https://mlsanity.com/paper/2604.15813/) (2026)
- [DataMagic: Authoring Data Videos through Declarative Multi-Agent Orchestration](https://mlsanity.com/paper/2609.33403/) (2026)

## Abstract (arXiv)

Data video is a media form that integrates data visualization with video narrative, widely adopted in news reporting and business analysis. Compared with general video understanding, data video understanding places greater emphasis on accurately reading data from animated charts, integrating evidence across charts and time, and understanding how narrative organization and visual design communicate information. Yet existing benchmarks target either general videos or static charts, and data video understanding has not been systematically evaluated. We present DataVista, the first benchmark for data video understanding, containing 961 real-world data videos and 6,775 evaluation questions organized under a three-level progressive capability framework (data perception, temporal reasoning, narrative understanding) with 10 fine-grained question types across five topic domains. Systematic evaluation of 19 mainstream MLLMs shows that the best-performing model, Gemini-3.1-Pro, achieves 70.0% overall accuracy, still far below human expert performance, with models performing worst on Causal Reasoning and Narrative Structure. Increasing frame counts and adding subtitles mainly benefit data perception and temporal reasoning, with limited gains in narrative understanding. Further analysis of model responses identifies typical failure modes in chart reading, evidence judgment, and instruction understanding. The benchmark is available at https://github.com/HKUSTDial/DataVista.