10 citations · 30 across the 11 of their papers we have counts for
4 papers · 1 filter
Investigating Mixture of Experts in Dense Retrieval
Effrosyni Sokli, Pranav Kasela, Georgios Peikos +1
While Dense Retrieval Models (DRMs) have advanced Information Retrieval (IR), one limitation of these neural models is their narrow generalizability and robustness. To cope with th…
Leveraging Large Language Models for Medical Information Extraction and Query Generation
Georgios Peikos, Pranav Kasela, Gabriella Pasi
This paper introduces a system that integrates large language models (LLMs) into the clinical trial retrieval process, enhancing the effectiveness of matching patients with eligibl…
Synthetic Data Generation with Large Language Models for Personalized Community Question Answering
Marco Braga, Pranav Kasela, Alessandro Raganato +1
Personalization in Information Retrieval (IR) is a topic studied by the research community since a long time. However, there is still a lack of datasets to conduct large-scale eval…
DESIRE-ME: Domain-Enhanced Supervised Information REtrieval using Mixture-of-Experts
Pranav Kasela, Gabriella Pasi, Raffaele Perego +1
Open-domain question answering requires retrieval systems able to cope with the diverse and varied nature of questions, providing accurate answers across a broad spectrum of query…