PaperPilot AI: An AI-Powered Multimodal Research Paper Mentor for Intelligent Academic Content Understanding, Mathematical Equation Decoding, and Comparative Literature Analysis

Abstract: PaperPilot AI is an end-to-end multimodal research paper mentorship and intelligent retrieval platform designed to accelerate scientific paper comprehension, mathematical formula deconstruction, and comparative literature analysis. Modern academic literature relies heavily on complex LaTeX equations, multi-axis figures, empirical benchmark tables, and specialized domain terminology that present severe barriers to students and researchers. PaperPilot AI addresses these challenges by combining PyMuPDF document extraction, regex-driven mathematical formula detection, a Retrieval-Augmented Generation (RAG) Q&A engine with page-level citations, and high-performance LLMs (Groq Llama 3.3 70B and heuristic professor fallbacks). The system features multi-tiered explanation modules ('Like I'm 15', 'College Student', 'Simple English', and 'Real-World Analogies'), line-by-line LaTeX variable symbol breakdowns with worked numerical examples, visual plot axis decoders, experimental table metric evaluators, automated research methodology flowcharts, interactive Anki flashcards, multi-type quiz generators (MCQ, True/False, Coding, Interview), and automated citation generators (BibTeX, APA, IEEE, MLA). Furthermore, the platform integrates a comparative literature engine that benchmarks paper contributions against baseline models. The system is delivered via a FastAPI backend and a modern React Vite frontend, offering a responsive, professor-grade interactive research companion.

Keywords: Research Paper Mentor, Retrieval-Augmented Generation (RAG), Multimodal LLM, LaTeX Equation Decoding, Figure & Table Intelligence, Comparative Literature Analysis, Automated Quiz & Flashcard Generation.