Edoardo D'Amico

23 papers A 4Misc 2Journal 14Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Unified Language Model for Large Scale Search, Recommendation, and Reasoning. CoRR Marco De Nadai, Edoardo D'Amico, Max Lefarov, Alexandre Tamborrino, Divita Vohra, Mark VanMiddlesworth, Shawn Lin, Jacqueline Wood, Jan Stypka, Eliza Klyce, Keshi Dai, Timothy Christopher Heath, Martin D. Gould, Yves Raimond, Sandeep Ghael, Tony Jebara, Andreas Damianou, Vladan Radosavljevic, Paul N. Bennett, Mounia Lalmas, Praveen Chandar
2026	J	`jnl`	Deploying Semantic ID-based Generative Retrieval for Large-Scale Podcast Discovery at Spotify. CoRR Edoardo D'Amico, Marco De Nadai, Praveen Chandar, Divita Vohra, Shawn Lin, Max Lefarov, Paul Gigioli, Gustavo Penha, Ilya Kopysitsky, Ivo Joel Senese, Darren Mei, Francesco Fabbri, Oguz Semerci, Yu Zhao, Vincent Tang, Brian St. Thomas, Alexandra Ranieri, Matthew N. K. Smith, Aaron Bernkopf, Bryan Leung, Ghazal Fazelnia, Mark VanMiddlesworth, Timothy Christopher Heath, Petter Pehrson Skidén, Alice Y. Wang, Doug J. Cole, Andreas Damianou, Maya Hristakeva, Reid Wilbur, Tarun Chillara, Vladan Radosavljevic, Pooja Chitkara, Sainath Adapa, Juan Elenter, Bernd Huber, Jacqueline Wood, Saaketh Vedantam, Jan Stypka, Sandeep Ghael, Martin D. Gould, David Murgatroyd, Yves Raimond, Mounia Lalmas, Paul N. Bennett
2026	J	`jnl`	Don't Get Bored: Enhancing Scalability and Diversity in Session-Based Slate Recommendation. Trans. Recomm. Syst. Aayush Singha Roy, Edoardo D'Amico, Elias Z. Tragos, Aonghus Lawlor, Neil Hurley
2025	J	`jnl`	Dataset-Agnostic Recommender Systems. CoRR Tri Kurniawan Wijaya, Edoardo D'Amico, Xinyang Shao
2025	J	`jnl`	Do LLM-judges Align with Human Relevance in Cranfield-style Recommender Evaluation? CoRR Gustavo Penha, Aleksandr V. Petrov, Claudia Hauff, Enrico Palumbo, Ali Vardasbi, Edoardo D'Amico, Francesco Fabbri, Alice Wang, Praveen Chandar, Henrik Lindström, Hugues Bouchard, Mounia Lalmas
2025	A	`conf`	Evaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge. RecSys Francesco Fabbri, Gustavo Penha, Edoardo D'Amico, Alice Wang, Marco De Nadai, Jackie Doremus, Paul Gigioli, Andreas Damianou, Oskar Stål, Mounia Lalmas
2025	J	`jnl`	Evaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge. CoRR Francesco Fabbri, Gustavo Penha, Edoardo D'Amico, Alice Wang, Marco De Nadai, Jackie Doremus, Paul Gigioli, Andreas Damianou, Oskar Stål, Mounia Lalmas
2025	A	`conf`	Semantic IDs for Joint Generative Search and Recommendation. RecSys Gustavo Penha, Edoardo D'Amico, Marco De Nadai, Enrico Palumbo, Alexandre Tamborrino, Ali Vardasbi, Max Lefarov, Shawn Lin, Timothy Christopher Heath, Francesco Fabbri, Hugues Bouchard
2025	J	`jnl`	Semantic IDs for Joint Generative Search and Recommendation. CoRR Gustavo Penha, Edoardo D'Amico, Marco De Nadai, Enrico Palumbo, Alexandre Tamborrino, Ali Vardasbi, Max Lefarov, Shawn Lin, Timothy Christopher Heath, Francesco Fabbri, Hugues Bouchard
2025	J	`jnl`	Universal Reusability in Recommender Systems: The Case for Dataset- and Task-Independent Frameworks. CoRR Tri Kurniawan Wijaya, Xinyang Shao, Gonzalo Fiz Pontiveros, Edoardo D'Amico
2024	J	`jnl`	RBoard: A Unified Platform for Reproducible and Reusable Recommender System Benchmarks. CoRR Xinyang Shao, Edoardo D'Amico, Gábor Fodor, Tri Kurniawan Wijaya
2024	A	`conf`	Rs4rs: Semantically Find Recent Publications from Top Recommendation System-Related Venues. RecSys Tri Kurniawan Wijaya, Edoardo D'Amico, Gábor Fodor, Manuel V. Loureiro
2024	J	`jnl`	Rs4rs: Semantically Find Recent Publications from Top Recommendation System-Related Venues. CoRR Tri Kurniawan Wijaya, Edoardo D'Amico, Gábor Fodor, Manuel V. Loureiro
2023	Misc	`conf`	Addressing Fast Changing Fashion Trends in Multi-Stage Recommender Systems. FLAIRS Aayush Singha Roy, Edoardo D'Amico, Aonghus Lawlor, Neil Hurley
2023	—	`conf`	Item Graph Convolution Collaborative Filtering for Inductive Recommendations. ECIR (1) Edoardo D'Amico, Khalil Muhammad, Elias Z. Tragos, Barry Smyth, Neil Hurley, Aonghus Lawlor
2023	J	`jnl`	Item Graph Convolution Collaborative Filtering for Inductive Recommendations. CoRR Edoardo D'Amico, Khalil Muhammad, Elias Z. Tragos, Barry Smyth, Neil Hurley, Aonghus Lawlor
2023	—	`conf`	Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation. PAKDD (3) Edoardo D'Amico, Aonghus Lawlor, Neil Hurley
2023	J	`jnl`	Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation. CoRR Edoardo D'Amico, Aonghus Lawlor, Neil Hurley
2023	A	`conf`	Scalable Deep Q-Learning for Session-Based Slate Recommendation. RecSys Aayush Singha Roy, Edoardo D'Amico, Elias Z. Tragos, Aonghus Lawlor, Neil Hurley
2022	J	`jnl`	Analyzing and improving stability of matrix factorization for recommender systems. J. Intell. Inf. Syst. Edoardo D'Amico, Giovanni Gabbolini, Cesare Bernardis, Paolo Cremonesi
2021	J	`jnl`	On the instability of embeddings for recommender systems: the case of Matrix Factorization. CoRR Giovanni Gabbolini, Edoardo D'Amico, Cesare Bernardis, Paolo Cremonesi
2021	Misc	`conf`	On the instability of embeddings for recommender systems: the case of matrix factorization. SAC Giovanni Gabbolini, Edoardo D'Amico, Cesare Bernardis, Paolo Cremonesi
2019	—	`conf`	Leveraging laziness, browsing-pattern aware stacked models for sequential accommodation learning to rank. RecSys Challenge Edoardo D'Amico, Giovanni Gabbolini, Daniele Montesi, Matteo Moreschini, Federico Parroni, Federico Piccinini, Alberto Rossettini, Alessio Russo Introito, Cesare Bernardis, Maurizio Ferrari Dacrema