108 citations · 444 across the 24 of their papers we have counts for
4 papers · 1 filter
RRAML: Reinforced Retrieval Augmented Machine Learning
Andrea Bacciu, Florin Cuconasu, Federico Siciliano +3
The emergence of large language models (LLMs) has revolutionized machine learning and related fields, showcasing remarkable abilities in comprehending, generating, and manipulating…
Integrating Item Relevance in Training Loss for Sequential Recommender Systems
Andrea Bacciu, Federico Siciliano, Nicola Tonellotto +1
Sequential Recommender Systems (SRSs) are a popular type of recommender system that learns from a user's history to predict the next item they are likely to interact with. However,…
A Federated Channel Modeling System using Generative Neural Networks
Saira Bano, Pietro Cassarà, Nicola Tonellotto +1
The paper proposes a data-driven approach to air-to-ground channel estimation in a millimeter-wave wireless network on an unmanned aerial vehicle. Unlike traditional centralized le…
A Static Pruning Study on Sparse Neural Retrievers
Carlos Lassance, Simon Lupart, Hervé Dejean +2
Sparse neural retrievers, such as DeepImpact, uniCOIL and SPLADE, have been introduced recently as an efficient and effective way to perform retrieval with inverted indexes. They a…