For Students

Ongoing Theses

• Halle
  • Building Medical Knowledge Graphs for Knowledge Injection in LLMs (supervised by Alexander Bondarenko and Jan Heinrich Merker)
• Jena
  • Evaluating Pre-Training Techniques for Single-Vector Encoder Models (supervised by Ferdinand Schlatt)
  • Testing the Limits of Multi-Vector Bi-Encoder Models (supervised by Ferdinand Schlatt)
  • Dense Boolean Retrieval for Systematic Reviews (supervised by Ferdinand Schlatt)
  • Improving Learned Lexical Retrieval Models by Removing Lexical Dependencies (supervised by Ferdinand Schlatt)
  • Reducing the Size of Dense Retrieval Indexes by Removing Unimportant Terms (supervised by Ferdinand Schlatt)
  • Argument Mining in the AQL (supervised by Ines Zelch)
  • Construction of Fine-Grained Retrieval Pipelines With PyTerrier (supervised by Maik Fröbe and Jan Heinrich Merker)
  • Agent-based Retrieval-Augmented Biomedical Question Answering (supervised by Jan Heinrich Merker and Wilhelm Pertsch)
• Leipzig
  • Extracting negated causal statements (supervised by Tim Hagen)
  • Facets of complexity in scholarly political language (supervised by Magdalena Wolska)
  • Simplifying the language of political argumentation (supervised by Magdalena Wolska)
  • Lightweight Passage Re-ranking Using Embeddings from Pre-trained Language Models (supervised by Ferdinand Schlatt and Harry Scells)
  • Logical Features of Neural Networks (supervised by Maximilian Heinrich)
  • Active Learning for Text Classification (supervised by Christian Kahmann and Christopher Schröder)
  • Incorporating Knowledge Graph Embeddings in Large Language Models (supervised by Ferdinand Schlatt)
  • Normdaten-Disambiguierung und Reconciliation auf Korpusdaten (supervised by Erik Körner and Felix Helfer)
  • Statistical Bootstrap Tests with Redundant Data (supervised by Maik Fröbe)
  • Mining Trigger Warnings from the Web and Social Media (supervised by Matti Wiegmann)
• Weimar
  • Employing Personal Knowledge Graphs in User Simulation in Conversational Search (supervised by Nailia Mirzakhmedova)
  • Building an Image Generator for Arguments (supervised by Maximilian Heinrich)
  • From Schemes to Fallacies: A Deep Dive into Argument Classification (supervised by Maximilian Heinrich)
  • Information Extraction from Scientific PDFs (supervised by Tim Gollub)
  • Adding Contextual Awareness to LLM-based Story Generation (supervised by Tim Gollub)
  • Prompt Framing Effects on Large Language Model Subjectivity Judgements (supervised by Nailia Mirzakhmedova)
  • How Humans Detect Cloned Voices (supervised by Johannes Kiesel and Marcel Gohsen)
  • Story Orchestration for Multi-Agent Collaboration for Automatic Story Generation (supervised by Marcel Gohsen)
  • Do Large Language Models Extrapolate Personas of Dialog Participants from Context? (supervised by Marcel Gohsen)
  • Developing a Teaching Assistant for Course Materials with Retrieval-Augmented Generation (supervised by Marcel Gohsen)
  • Crafting Multi-Modal Learning Experiences based on Course Materials (supervised by Marcel Gohsen)
  • Topic Segmentation with Large Language Models (supervised by Johannes Kiesel)
  • Efficient and Effective Neural Translation Language Model for Search (supervised by Harry Scells)
  • Rating the Degree of Search Engine Optimization of Websites (supervised by Janek Bevendorff)
  • Personalizing Question Answering (supervised by Matti Wiegmann and Marcel Gohsen)