2 citations · 2 across the 1 of their papers we have counts for
4 papers
Towards End-to-End Model-Agnostic Explanations for RAG Systems
Viju Sudhi, Sinchana Ramakanth Bhat, Max Rudat +2
Retrieval Augmented Generation (RAG) systems, despite their growing popularity for enhancing model response reliability, often struggle with trustworthiness and explainability. In…
Rethinking Chunk Size For Long-Document Retrieval: A Multi-Dataset Analysis
Sinchana Ramakanth Bhat, Max Rudat, Jannis Spiekermann +1
Chunking is a crucial preprocessing step in retrieval-augmented generation (RAG) systems, significantly impacting retrieval effectiveness across diverse datasets. In this study, we…
Fact Finder -- Enhancing Domain Expertise of Large Language Models by Incorporating Knowledge Graphs
Daniel Steinigen, Roman Teucher, Timm Heine Ruland +6
Recent advancements in Large Language Models (LLMs) have showcased their proficiency in answering natural language queries. However, their effectiveness is hindered by limited doma…
Integrating Generative Artificial Intelligence in Intelligent Vehicle Systems
Lukas Stappen, Jeremy Dillmann, Serena Striegel +3
This paper aims to serve as a comprehensive guide for researchers and practitioners, offering insights into the current state, potential applications, and future research direction…