204 citations · 206 across the 9 of their papers we have counts for
12 papers
A Picture of Agentic Search
Francesca Pezzuti, Ophir Frieder, Fabrizio Silvestri +2
With automated systems increasingly issuing search queries alongside humans, Information Retrieval (IR) faces a major shift. Yet IR remains human-centred, with systems, evaluation…
Statistical Foundations of DIME: Risk Estimation for Practical Index Selection
Giulio D'Erasmo, Cesare Campagnano, Antonio Mallia +3
High-dimensional dense embeddings have become central to modern Information Retrieval, but many dimensions are noisy or redundant. Recently proposed DIME (Dimension IMportance Esti…
Early-Exit Graph Neural Networks
Andrea Giuseppe Di Francesco, Maria Sofia Bucarelli, Franco Maria Nardini +3
Early-exit mechanisms allow deep neural networks to stop inference once prediction confidence is high, reducing latency and energy on easy inputs while retaining full-depth accurac…
AMAQA: A Metadata-based QA Dataset for RAG Systems
Davide Bruni, Marco Avvenuti, Nicola Tonellotto +1
Retrieval-augmented generation (RAG) systems are widely used in question-answering (QA) tasks, but current benchmarks lack metadata integration, limiting their evaluation in scenar…
Exploring the Effectiveness of Multi-stage Fine-tuning for Cross-encoder Re-rankers
Francesca Pezzuti, Sean MacAvaney, Nicola Tonellotto
State-of-the-art cross-encoders can be fine-tuned to be highly effective in passage re-ranking. The typical fine-tuning process of cross-encoders as re-rankers requires large amoun…
ECLIPSE: Contrastive Dimension Importance Estimation with Pseudo-Irrelevance Feedback for Dense Retrieval
Giulio D'Erasmo, Giovanni Trappolini, Nicola Tonellotto +1
Recent advances in Information Retrieval have leveraged high-dimensional embedding spaces to improve the retrieval of relevant documents. Moreover, the Manifold Clustering Hypothes…