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Our hybrid approach uses both fast heuristic analysis and a lightweight AI model to identify and classify headings (Title, H1, H2, H3), delivering reliable results in seconds.\r\n\r\n  * **Challenge 1B: Persona-Driven Document Intelligence**\r\n    We developed an intelligent system that analyzes a collection of PDFs to find the most relevant information for a user's specific job. The solution uses a sentence transformer model to prioritize sections based on a given persona and task, generating a structured output for easy consumption.\r\n\r\nYou can find the full documentation and code in the respective challenge folders below.\r\n\r\n  * **[Challenge 1A Folder](https://github.com/exploring-solver/adobe-hackathon-2025/tree/main/Challenge_1a)**\r\n  * **[Challenge 1B Folder](https://github.com/exploring-solver/adobe-hackathon-2025/tree/main/Challenge_1b)**\r\n\r\nMade by [@ivar03](https://www.google.com/search?q=https://github.com/ivar03) and [@exploring-solver](https://github.com/exploring-solver).\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fexploring-solver%2Fadobe-hackathon-2025","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fexploring-solver%2Fadobe-hackathon-2025","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fexploring-solver%2Fadobe-hackathon-2025/lists"}