VincentGranville/Large-Language-Models
xLLM 1.0, smart crawling, knowledge graph discovery.
This project helps researchers, data scientists, and students in statistics and probability create more effective search queries and prompts for AI models. It takes data from academic directories like Wolfram MathWorld and transforms it into structured categories and rich word embeddings. The output is a set of enhanced prompts designed to improve results from platforms like GPT, Wikipedia, ArXiv, Google Scholar, and Stack Exchange.
472 stars. No commits in the last 6 months.
Use this if you need to generate highly relevant and enriched prompts for large language models and search engines in the domain of probability and statistics.
Not ideal if your primary interest lies outside of probability and statistics or if you require an off-the-shelf application rather than a foundational architecture for prompt engineering.
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472
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135
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Last pushed
Jul 13, 2025
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