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Curlie Enhanced with LLM Annotations: Two Datasets for Advancing Homepage2Vec's Multilingual Website Classification

<h3>Advancing Homepage2Vec with LLM-Generated Datasets for Multilingual Website Classification</h3> <p>This dataset contains two subsets of labeled website data, specifically created to enhance the performance of Homepage2Vec, a multi-label model for website classification. The datasets were generated using Large Language Models (LLMs) to provide more accurate and diverse topic annotations for websites, addressing a limitation of existing Homepage2Vec training data.</p> <p><strong>Key Features:</strong></p> <ul> <li><strong>LLM-generated annotations:</strong>&nbsp;Both datasets feature website topic labels generated using LLMs,&nbsp;a novel approach to creating high-quality training data for website classification models.</li> <li><strong>Improved multi-label classification:</strong> Fine-tuning Homepage2Vec with these datasets has been shown to improve its macro F1 score from 38% to 43% evaluated on a human-labeled dataset, demonstrating their effectiveness in capturing a broader range of website topics.</li> <li><strong>Multilingual applicability:</strong> The datasets facilitate classification of websites in multiple languages, reflecting the inherent multilingual nature of Homepage2Vec.</li> </ul> <p><strong>Dataset Composition:</strong></p> <ul> <li><strong>curlie-gpt3.5-10k:</strong> 10,000 websites labeled using GPT-3.5, context 2 and 1-shot</li> <li><strong>curlie-gpt4-10k:</strong> 10,000 websites labeled using GPT-4, context 2 and zero-shot</li> </ul> <p><strong>Intended Use:</strong></p> <ul> <li>Fine-tuning and advancing Homepage2Vec or similar website classification models</li> <li>Research on LLM-generated datasets for text classification tasks</li> <li>Exploration of multilingual website classification</li> </ul> <p><strong>Additional Information:</strong></p> <ul> <li><strong>Project and report repository:</strong> https://github.com/CS-433/ml-project-2-mlp</li> </ul> <p><strong>Acknowledgments:</strong></p> <p>This dataset was created as part of a project at EPFL's Data Science Lab (DLab) in collaboration with <a href="https://people.epfl.ch/robert.west">Prof. Robert West</a> and <a href="https://tizianopiccardi.github.io/" rel="nofollow">Tiziano Piccardi.</a></p>