Study Project: LLMs for Science
Master's Study Project, Osnabrück University, 2024
Managed and organized a study project focused on “Supporting the Review Process with AI” - an AI-driven system developed by master’s students to assist with the academic reviewing process.
Project Overview
Our AI-driven system automates source validation by verifying the accuracy of citations against their original sources and facilitates literature discovery by identifying relevant scientific papers for a given topic. Additionally, the system aims to make the argument structure easier to digest and analyze by turning the contents of the paper into a graph database. This project aims to streamline the review process, enhance citation accuracy, and support high-quality academic work through practical AI applications.
Key Functionalities
🔍 Citation Verification & Source Analysis
The system extracts references from uploaded research papers and automatically retrieves the original sources. Using AI-based text analysis, it evaluates how accurately and contextually correct the sources are cited. This ensures citation integrity, reduces the risk of misrepresentation, and provides structured feedback to enhance academic precision.
🧠 Paper Knowledge Graphs
The system transforms the content of research papers into a graph database, representing the relationships between different concepts, arguments, and evidence. This visualization aids in understanding complex arguments and facilitates deeper analysis, making it easier for reviewers to navigate through the paper’s structure and logic.
📚 AI-driven Literature Discovery
Given a scientific topic, the system searches across multiple academic databases to identify high-quality and relevant research papers. The AI ranks sources based on credibility, relevance, and recent advancements, helping researchers efficiently find the most suitable literature for their work.
Key Responsibilities
- Led and coordinated the study project activities
- Managed student teams and research directions
- Facilitated collaboration between AI and scientific domains
- Oversaw project deliverables and outcomes
Technical Focus
- Large Language Models (LLMs) for scientific applications
- Citation verification and source analysis
- Knowledge graph construction from research papers
- AI-driven literature discovery and recommendation
- Academic review process automation
Project Partners
- Institute of Information Management and Information Systems (IMWI) at University of Osnabrück, led by Professor Dr. Oliver Thomas
- Autonomous Empirical Research Group (AER), led by Sebastian Musslick