FullFront: Benchmarking MLLMs Across the Full Front-End Engineering Workflow

FullFront is a new benchmark that evaluates Multimodal Large Language Models (MLLMs) across the entire front‑end engineering workflow, covering webpage design, perception QA, and code generation. It uses a two‑stage process to convert real‑world webpages into clean, standardized HTML, avoiding copyright issues and providing diverse visual designs. Experiments show that current MLLMs struggle with page perception, image handling, layout, and interaction implementation, revealing a large gap compared to human experts.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

• llms
• multimodal
• benchmarks