1 citations · 2 across the 3 of their papers we have counts for
3 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…