Assessing the Impact of a User-Item Collaborative Attack on Class of Users. - Yashar Deldjoo; Tommaso Di Noia; Felice Antonio Merra (ImpactRS@RecSys, 2019)

Assessing Perceptual and Recommendation Mutation of Adversarially-Poisoned Visual Recommenders (short paper). - Vito Walter Anelli; Tommaso Di Noia; Daniele Malitesta; Felice Antonio Merra (DP@AI*IA, 2020)

TAaMR: Targeted Adversarial Attack against Multimedia Recommender Systems. - Tommaso Di Noia; Daniele Malitesta; Felice Antonio Merra (DSN Workshops, 2020)

SAShA: Semantic-Aware Shilling Attacks on Recommender Systems Exploiting Knowledge Graphs. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Eugenio Di Sciascio; Felice Antonio Merra (ESWC, 2020)

Adversarial Learning for Recommendation: Applications for Security and Generative Tasks - Concept to Code. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Felice Antonio Merra (RecSys, 2020)

Knowledge-enhanced Shilling Attacks for Recommendation. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Felice Antonio Merra; Giuseppe Acciani; Eugenio Di Sciascio (SEBD, 2020)

How Dataset Characteristics Affect the Robustness of Collaborative Recommendation Models. - Yashar Deldjoo; Tommaso Di Noia; Eugenio Di Sciascio; Felice Antonio Merra (SIGIR, 2020)

Adversarial Machine Learning in Recommender Systems (AML-RecSys). - Yashar Deldjoo; Tommaso Di Noia; Felice Antonio Merra (WSDM, 2020)

Adversarial Machine Learning in Recommender Systems: State of the art and Challenges. - Yashar Deldjoo; Tommaso Di Noia; Felice Antonio Merra (CoRR, 2020)

An Empirical Study of DNNs Robustification Inefficacy in Protecting Visual Recommenders. - Vito Walter Anelli; Tommaso Di Noia; Daniele Malitesta; Felice Antonio Merra (CoRR, 2020)

Multi-Step Adversarial Perturbations on Recommender Systems Embeddings. - Vito Walter Anelli; Alejandro Bellogín; Yashar Deldjoo; Tommaso Di Noia; Felice Antonio Merra (CoRR, 2020)

A Formal Analysis of Recommendation Quality of Adversarially-trained Recommenders. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Felice Antonio Merra (CIKM, 2021)

A Study on the Relative Importance of Convolutional Neural Networks in Visually-Aware Recommender Systems. - Yashar Deldjoo; Tommaso Di Noia; Daniele Malitesta; Felice Antonio Merra (CVPR Workshops, 2021)

MSAP: Multi-Step Adversarial Perturbations on Recommender Systems Embeddings. - Vito Walter Anelli; Alejandro Bellogín; Yashar Deldjoo; Tommaso Di Noia; Felice Antonio Merra (FLAIRS, 2021)

How to Perform Reproducible Experiments in the ELLIOT Recommendation Framework: Data Processing, Model Selection, and Performance Evaluation. - Vito Walter Anelli; Alejandro Bellogín; Antonio Ferrara 001; Daniele Malitesta; Felice Antonio Merra; Claudio Pomo; Francesco Maria Donini; Eugenio Di Sciascio; Tommaso Di Noia (IIR, 2021)

A Regression Framework to Interpret the Robustness of Recommender Systems Against Shilling Attacks. - Yashar Deldjoo; Tommaso Di Noia; Eugenio Di Sciascio; Felice Antonio Merra (IIR, 2021)

V-Elliot: Design, Evaluate and Tune Visual Recommender Systems. - Vito Walter Anelli; Alejandro Bellogín; Antonio Ferrara 001; Daniele Malitesta; Felice Antonio Merra; Claudio Pomo; Francesco Maria Donini; Tommaso Di Noia (RecSys, 2021)

The Idiosyncratic Effects of Adversarial Training on Bias in Personalized Recommendation Learning. - Vito Walter Anelli; Tommaso Di Noia; Felice Antonio Merra (RecSys, 2021)

Adversarial Attacks against Visual Recommendation: an Investigation on the Influence of Items' Popularity. - Vito Walter Anelli; Tommaso Di Noia; Eugenio Di Sciascio; Daniele Malitesta; Felice Antonio Merra (OHARS@RecSys, 2021)

AMFLP: Adversarial Matrix Factorization-based Link Predictor in Social Graphs. - Giuseppe De Candia; Tommaso Di Noia; Eugenio Di Sciascio; Felice Antonio Merra (SEBD, 2021)

Elliot: A Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation. - Vito Walter Anelli; Alejandro Bellogín; Antonio Ferrara 001; Daniele Malitesta; Felice Antonio Merra; Claudio Pomo; Francesco Maria Donini; Tommaso Di Noia (SIGIR, 2021)

A Study of Defensive Methods to Protect Visual Recommendation Against Adversarial Manipulation of Images. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Daniele Malitesta; Felice Antonio Merra (SIGIR, 2021)

Understanding the Effects of Adversarial Personalized Ranking Optimization Method on Recommendation Quality. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Felice Antonio Merra (CoRR, 2021)

Leveraging Content-Style Item Representation for Visual Recommendation. - Yashar Deldjoo; Tommaso Di Noia; Daniele Malitesta; Felice Antonio Merra (ECIR (2), 2022)

The Challenging Reproducibility Task in Recommender Systems Research between Traditional and Deep Learning Models. - Vito Walter Anelli; Alejandro Bellogín; Antonio Ferrara 001; Daniele Malitesta; Felice Antonio Merra; Claudio Pomo; Francesco M. Donini; Eugenio Di Sciascio; Tommaso Di Noia (SEBD, 2022)

Search Filter Ranking with Language-Aware Label Embeddings. - Jacek Golebiowski; Felice Antonio Merra; Ziawasch Abedjan; Felix Biessmann (WWW (Companion Volume), 2022)

A Survey on Adversarial Recommender Systems: From Attack/Defense Strategies to Generative Adversarial Networks. - Yashar Deldjoo; Tommaso Di Noia; Felice Antonio Merra (ACM Comput. Surv., 2022)

Adversarial Recommender Systems: Attack, Defense, and Advances. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Felice Antonio Merra (Recommender Systems Handbook, 2022)

Denoise to Protect: A Method to Robustify Visual Recommenders from Adversaries. - Felice Antonio Merra; Vito Walter Anelli; Tommaso Di Noia; Daniele Malitesta; Alberto Carlo Maria Mancino (SIGIR, 2023)

Improving the Relevance of Product Search for Queries with Negations. - Felice Antonio Merra; Omar Zaidan; Fabricio de Sousa Nascimento (WWW (Companion Volume), 2023)

Adversarial Machine Learning in Recommender Systems. - Felice Antonio Merra (SIGIR Forum, 2023)

Empowering Shilling Attacks with Katz and Exclusivity-based Relatedness. - Felice Antonio Merra; Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Eugenio Di Sciascio (KaRS@RecSys, 2024)

Hyperband-based Bayesian Optimization for Black-box Prompt Selection. - Lennart Schneider; Martin Wistuba; Aaron Klein; Jacek Golebiowski; Giovanni Zappella; Felice Antonio Merra (CoRR, 2024)

Do LLMs Memorize Recommendation Datasets? A Preliminary Study on MovieLens-1M. - Dario Di Palma; Felice Antonio Merra; Maurizio Sfilio; Vito Walter Anelli; Fedelucio Narducci; Tommaso Di Noia (SIGIR, 2025)

Formalizing Multimedia Recommendation through Multimodal Deep Learning. - Daniele Malitesta; Giandomenico Cornacchia; Claudio Pomo; Felice Antonio Merra; Tommaso Di Noia; Eugenio Di Sciascio (Trans. Recomm. Syst., 2025)