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SEMA

csvl / SEMA

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SEMA is based on angr, a symbolic execution engine used to extract API calls. Especially, we extend ANGR with strategies to create representative signatures based on System Call Dependency graph (SCDG). Those SCDGs can be exploited in machine learning modules to do classification/detection.

python windows linux detection static-analysis reverse-engineering malware symbolic-execution symbolic cybersecurity classification reverse ctf malware-analysis binary-analysis malware-research angr concolic-execution malware-detection sema
  • Updated Mar 10, 2025
  • Python

udhaya2823 / Retrieval-Augmented-Generation-based-AI-Research-paper-Assistant

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🎯This project is a Retrieval-Augmented Generation (RAG) application designed to help researchers, students, and AI enthusiasts efficiently extract insights from complex AI research papers. By leveraging semantic search and generative AI, users can upload research papers, ask questions, and receive precise, context-aware answers.

artificial-intelligence gradio sema rag large-language-models retrieval-augmented-generation
  • Updated Mar 11, 2025
  • Jupyter Notebook

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