2 citations · 2 across the 2 of their papers we have counts for
4 papers · 1 filter
LiveRAG: A diverse Q&A dataset with varying difficulty level for RAG evaluation
David Carmel, Simone Filice, Guy Horowitz +4
With Retrieval Augmented Generation (RAG) becoming more and more prominent in generative AI solutions, there is an emerging need for systematically evaluating their effectiveness.…
SIGIR 2025 -- LiveRAG Challenge Report
David Carmel, Simone Filice, Guy Horowitz +6
The LiveRAG Challenge at SIGIR 2025, held between March and May 2025, provided a competitive platform for advancing Retrieval-Augmented Generation (RAG) technologies. Participants…
Do RAG Systems Really Suffer From Positional Bias?
Florin Cuconasu, Simone Filice, Guy Horowitz +2
Retrieval Augmented Generation enhances LLM accuracy by adding passages retrieved from an external corpus to the LLM prompt. This paper investigates how positional bias - the tende…
Generating Diverse Q&A Benchmarks for RAG Evaluation with DataMorgana
Simone Filice, Guy Horowitz, David Carmel +3
Evaluating Retrieval-Augmented Generation (RAG) systems, especially in domain-specific contexts, requires benchmarks that address the distinctive requirements of the applicative sc…