10 citations · 15 across the 10 of their papers we have counts for
4 papers · 1 filter
RAGognizer: Hallucination-Aware Fine-Tuning via Detection Head Integration
Fabian Ridder, Laurin Lessel, Malte Schilling
Retrieval-Augmented Generation (RAG) is widely used to augment the input to Large Language Models (LLMs) with external information, such as recent or domain-specific knowledge. Non…
Classifying German Language Proficiency Levels Using Large Language Models
Elias-Leander Ahlers, Witold Brunsmann, Malte Schilling
Assessing language proficiency is essential for education, as it enables instruction tailored to learners needs. This paper investigates the use of Large Language Models (LLMs) for…
The HalluRAG Dataset: Detecting Closed-Domain Hallucinations in RAG Applications Using an LLM's Internal States
Fabian Ridder, Malte Schilling
Detecting hallucinations in large language models (LLMs) is critical for enhancing their reliability and trustworthiness. Most research focuses on hallucinations as deviations from…
Evaluating the Impact of Advanced LLM Techniques on AI-Lecture Tutors for a Robotics Course
Sebastian Kahl, Felix Löffler, Martin Maciol +6
This study evaluates the performance of Large Language Models (LLMs) as an Artificial Intelligence-based tutor for a university course. In particular, different advanced techniques…