Introduces ProductWebGen benchmark for multimodal product webpage generation, compares editing-based vs unified-model workflows on 500 samples, and releases ProductWebGen-1k SFT dataset.
Sketch2code: Generating a website from a paper mockup
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
abstract
An early stage of developing user-facing applications is creating a wireframe to layout the interface. Once a wireframe has been created it is given to a developer to implement in code. Developing boiler plate user interface code is time consuming work but still requires an experienced developer. In this dissertation we present two approaches which automates this process, one using classical computer vision techniques, and another using a novel application of deep semantic segmentation networks. We release a dataset of websites which can be used to train and evaluate these approaches. Further, we have designed a novel evaluation framework which allows empirical evaluation by creating synthetic sketches. Our evaluation illustrates that our deep learning approach outperforms our classical computer vision approach and we conclude that deep learning is the most promising direction for future research.
verdicts
UNVERDICTED 2representative citing papers
Generative interfaces let LLMs create task-specific UIs that users prefer up to 72% more than standard chat responses across tested tasks.
citing papers explorer
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ProductWebGen: Benchmarking Multimodal Product Webpage Generation
Introduces ProductWebGen benchmark for multimodal product webpage generation, compares editing-based vs unified-model workflows on 500 samples, and releases ProductWebGen-1k SFT dataset.
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Generative Interfaces for Language Models
Generative interfaces let LLMs create task-specific UIs that users prefer up to 72% more than standard chat responses across tested tasks.