IIR 2024
Italian Information Retrieval Workshop 2024

Table of Contents

• Preface I
  Summary: There were 28 papers submitted to this workshop. All papers were peer-reviewed by three reviewers. Out of these, 23 were accepted for this volume, 5 as full papers, 1 as short paper, and 17 as extended abstracts.

Keynotes

• Data Protection in Data-Driven IR Systems 1
  Asia J. Biega
• Search Personalization: Which Information and How? 2
  Gabriella Pasi

Full Papers

• Beyond Conventional Metrics: Assessing User Simulators in Information Retrieval 3-12
  Saber Zerhoudi, Michael Granitzer
• Beyond Words: Can ChatGPT Support State-of-the-Art Recommender Systems? 13-22
  Dario Di Palma, Giovanni Servedio, Vito Walter Anelli, Giovanni Maria Biancofiore, Fedelucio Narducci, Leonarda Carnimeo, Tommaso Di Noia
• Comparatively Assessing Large Language Models for Query Expansion in Information Retrieval via Zero-Shot and Chain-of-Thought Prompting 23-32
  Daniele Rizzo, Alessandro Raganato, Marco Viviani
• LongDoc Summarization using Instruction-tuned Large Language Models for Food Safety Regulations 33-42
  Guido Rocchietti, Cosimo Rulli, Korbinian Randl, Cristina Ioana Muntean, Franco Maria Nardini Raffaele Perego, Salvatore Trani, Manos Karvounis, Jakub Janostik
• On the Application of a Common Theoretical Explainability Framework in Information Retrieval 43-52
  Andrea Albarelli, Claudio Lucchese, Matteo Rizzo, Alberto Veneri

Short Papers

• Beyond the Parameters: Measuring Actual Privacy in Obfuscated Texts 53-57
  Francesco Luigi De Faveri, Guglielmo Faggioli, Nicola Ferro

Extended Abstracts

• A Quantum Annealing-Based Instance Selection Approach for Transformer Fine-Tuning 58-61
  Andrea Pasin, Washington Cunha, Marcos André Gonçalves, Nicola Ferro
• Comprehensive Assessment of Robustness in Fairness of GNN-based Recommender Systems against Attacks 62-65
  Ludovico Boratto, Francesco Fabbri, Gianni Fenu, Mirko Marras, Giacomo Medda
• Content Representation and Analysis: the Magic Project and the Illuminated Dante Project Integrated Systems for Multimedia Information Retrieval 66-69
  Stefania Conte, Gennaro Ferrante, Lorenza Laccetti, Andrea Mazzucchi, Yahya Momtaz, Augusto Tortora
• Conversational-Agent for Patient Information Leaflet 70-73
  Riccardo Lunardi, Paolo Coppola
• Enhancing Fact-Checking: From Crowdsourced Validation to Integration with Large Language Models 74-77
  Kevin Roitero, Michael Soprano, David La Barbera, Eddy Maddalena, Stefano Mizzaro
• Finite Rank-Biased Overlap (FRBO): A New Measure for Stability in Sequential Recommender Systems 78-81
  Filippo Betello, Federico Siciliano, Pushkar Mishra, Fabrizio Silvestri
• Incorporating Cognitive Complexity of Text in Dense Retrieval for Personalized Search 82-85
  Effrosyni Sokli, Alessandro Raganato, Gabriella Pasi
• LambdaFair: a Fair and Effective LambdaMART 86
  Federico Marcuzzi, Claudio Lucchese, Salvatore Orlando
• Leveraging Semantic Embeddings of User Reviews with Off-the-Shelf LLMs for Recommender Systems 87-90
  Nicola Cecere, Andrea Pisani, Maurizio Ferrari Dacrema, Paolo Cremonesi
• Pre-Trained LLM Embeddings of Product Reviews for Recommendation 91-94
  Andrea Pisani, Nicola Cecere, Maurizio Ferrari Dacrema, Paolo Cremonesi
• Rethinking Relevance: How Noise and Distractors Impact Retrieval-Augmented Generation 95-98
  Florin Cuconasu, Giovanni Trappolini, Federico Siciliano, Simone Filice, Cesare Campagnano, Yoelle Mareek, Nicola Tonellotto, Fabrizio Silvestri
• SE-PQA: StackExchange Personalized Community Question Answering 99-102
  Pranav Kasela, Marco Braga, Gabriella Pasi, Raffaele Perego
• Seismic: Efficient and Effective Retrieval over Learned Sparse Representation 103-106
  Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini
• The CAMEO Project: A Holistic View for Conversational Agents 107-110
  Tommaso Di Noia, Guglielmo Faggioli, Marco Ferrante, Nicola Ferro, Fedelucio Narducci, Raffaele Perego, Giuseppe Santucci
• Toward Effective Fashion Item Compatibility Modelling 111-114
  Matteo Attimonelli, Claudio Pomo, Dietmar Jannach, Tommaso Di Noia
• Turning on a DIME: Estimating Dimension Importance for Dense Information Retrieval 115-118
  Guglielmo Faggioli, Nicola Ferro, Raffaele Perego, Nicola Tonellotto
• Unveiling the Potential of Recommender Systems through Multi-Objective Metrics 119-122
  Vincenzo Paparella, Dario Di Palma, Vito Walter Anelli, Alessandro De Bellis, Tommaso Di Noia