1 citations · 1 across the 2 of their papers we have counts for
3 papers
A Tale of Trust and Accuracy: Base vs. Instruct LLMs in RAG Systems
Florin Cuconasu, Giovanni Trappolini, Nicola Tonellotto +1
Retrieval Augmented Generation (RAG) represents a significant advancement in artificial intelligence combining a retrieval phase with a generative phase, with the latter typically…
Graph Neural Re-Ranking via Corpus Graph
Andrea Giuseppe Di Francesco, Christian Giannetti, Nicola Tonellotto +1
Re-ranking systems aim to reorder an initial list of documents to satisfy better the information needs associated with a user-provided query. Modern re-rankers predominantly rely o…
Generating Query Recommendations via LLMs
Andrea Bacciu, Enrico Palumbo, Andreas Damianou +2
Query recommendation systems are ubiquitous in modern search engines, assisting users in producing effective queries to meet their information needs. However, these systems require…