# WebVR: Benchmarking Multimodal LLMs for WebPage Recreation from Videos via Human-Aligned Visual Rubrics

arXiv: https://arxiv.org/abs/2603.13391 · HTML: https://mlsanity.com/paper/2603.13391/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Placed in Chart understanding and anomaly detection, one of 16 directions in Multimodal LLMs / vision-language models.
- Builds on 23 of its 26 references that are in the map.
- First posted on arXiv 11 Mar 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, 23 of 23)

- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena](https://mlsanity.com/paper/2306.05685/) (2023)
- [Qwen3-VL Technical Report](https://mlsanity.com/paper/2511.21631/) (2025)
- [Video-LLaVA: Learning United Visual Representation by Alignment Before Projection](https://mlsanity.com/paper/2311.10122/) (2023)
- [Large Language Models are not Fair Evaluators](https://mlsanity.com/paper/2305.17926/) (2023)
- [A Comprehensive Overview of Large Language Models](https://mlsanity.com/paper/2307.06435/) (2023)
- [Kimi K2.5: Visual Agentic Intelligence](https://mlsanity.com/paper/2602.02276/) (2026)
- [MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark](https://mlsanity.com/paper/2402.04788/) (2024)
- [Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset](https://mlsanity.com/paper/2403.09029/) (2024)
- [Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs](https://mlsanity.com/paper/2406.20098/) (2024)
- [WebGen-Bench: Evaluating LLMs on Generating Interactive and Functional Websites from Scratch](https://mlsanity.com/paper/2505.03733/) (2025)
- [Interaction2Code: Benchmarking MLLM-based Interactive Webpage Code Generation from Interactive Prototyping](https://mlsanity.com/paper/2411.03292/) (2024)
- [DesignBench: A Comprehensive Benchmark for MLLM-based Front-end Code Generation](https://mlsanity.com/paper/2506.06251/) (2025)
- [ArtifactsBench: Bridging the Visual-Interactive Gap in LLM Code Generation Evaluation](https://mlsanity.com/paper/2507.04952/) (2025)
- [Web-Bench: A LLM Code Benchmark Based on Web Standards and Frameworks](https://mlsanity.com/paper/2505.07473/) (2025)
- [STEP3-VL-10B Technical Report](https://mlsanity.com/paper/2601.09668/) (2026)
- [FullFront: Benchmarking MLLMs Across the Full Front-End Engineering Workflow](https://mlsanity.com/paper/2505.17399/) (2025)
- [WebCoderBench: Benchmarking Web Application Generation with Comprehensive and Interpretable Evaluation Metrics](https://mlsanity.com/paper/2601.02430/) (2026)
- [WebUIBench: A Comprehensive Benchmark for Evaluating Multimodal Large Language Models in WebUI-to-Code](https://mlsanity.com/paper/2506.07818/) (2025)
- [MLLM as a UI Judge: Benchmarking Multimodal LLMs for Predicting Human Perception of User Interfaces](https://mlsanity.com/paper/2510.08783/) (2025)
- [WebDevJudge: Evaluating (M)LLMs as Critiques for Web Development Quality](https://mlsanity.com/paper/2510.18560/) (2025)
- [Benchmarking MLLM-based Web Understanding: Reasoning, Robustness and Safety](https://mlsanity.com/paper/2509.21782/) (2025)
- [GUI-GenBench: Evaluating Image Generation Models as Interactive GUI Environments](https://mlsanity.com/paper/2602.09007/) (2026)

## Built on by (most cited first, 8 of 8)

- [Vision2Web: A Hierarchical Benchmark for Visual Website Development with Agent Verification](https://mlsanity.com/paper/2603.26648/) (2026)
- [VideoCoCo: Code-as-CoT for Physically-Consistent Video Generation via an Agentic Dual-Engine System](https://mlsanity.com/paper/2607.27380/) (2026)
- [EvoStreaming: Your Offline Video Model Is a Natively Streaming Assistant](https://mlsanity.com/paper/2605.10343/) (2026)
- [VideoVIBE: A Video-Grounded Diagnostic Benchmark for One-Shot Interactive Website Generation](https://mlsanity.com/paper/2608.09573/) (2026)
- [Omni2Web: Benchmarking Audiovisual Website Development](https://mlsanity.com/paper/2609.23417/) (2026)
- [Animation2Code: Evaluating Temporal Visual Reasoning in Video-to-Code Generation](https://mlsanity.com/paper/2606.28593/) (2026)
- [UI2App: Benchmarking Visual Interaction Inference in Executable Web Application Generation](https://mlsanity.com/paper/2607.06306/) (2026)
- [A2Z GameSpec-Bench: How Faithfully Can Coding Agents Generate Games from Game Design Specifications?](https://mlsanity.com/paper/2609.39564/) (2026)

## Abstract (arXiv)

Existing web-generation benchmarks rely on text prompts or static screenshots as input. However, videos naturally convey richer signals such as interaction flow, transition timing, and motion continuity, which are essential for faithful webpage recreation. Despite this potential, video-conditioned webpage generation remains largely unexplored, with no dedicated benchmark for this task. To fill this gap, we introduce WebVR, a benchmark that evaluates whether MLLMs can faithfully recreate webpages from demonstration videos. WebVR contains 175 webpages across diverse categories, all constructed through a controlled synthesis pipeline rather than web crawling, ensuring varied and realistic demonstrations without overlap with existing online pages. We also design a fine-grained, human-aligned visual rubric that evaluates the generated webpages across multiple dimensions. Experiments on 19 models reveal substantial gaps in recreating fine-grained style and motion quality, while the rubric-based automatic evaluation achieves 96% agreement with human preferences. We release the dataset, evaluation toolkit, and baseline results to support future research on video-to-webpage generation.