PaperFilter is a project designed to filter and classify research papers based on their relevance to a specified domain. This tool leverages a Large Language Model (LLM) to analyze paper abstracts and determine their alignment with the user's specified area of interest. The core functionality involves prompting the LLM with paper abstracts and receiving responses that classify the papers as relevant or not, along with explanations.

• Domain-Specific Filtering: The system can classify papers based on specific research domains, ensuring that only relevant papers are considered.
• Automated Classification: Utilizes an advanced LLM to automatically interpret the relevance of papers, reducing the manual effort required for initial filtering.
• Detailed Responses: For each paper, the system provides a classification along with a detailed explanation, aiding in understanding the reasoning behind the classification.