Publications

Sep 28, 2026|Presented: RecSys - USRW (Unified Search & Recommendation) Workshop
Robust Fusion of Semantic and Behavioural Signals for LLM Reranking in Personalised Search
Aleksandr V. Petrov, Nathan Stein, Erik Lybecker, Emma Schüldt, Daniel Lazarovski, Hugues Bouchard, Mounia Lalmas
Sep 25, 2026|RecSys
Intent-Description Anchoring Bias in LLM-as-a-Judge Evaluation of Recommendation Systems
Himan Abdollahpouri, Kyle Kretschman, Mounia Lalmas
Sep 25, 2026|RecSys - CONSEQUENCES Workshop
Incremental Recommendation via Causal Models
Athanasios Vlontzos, David Gustafsson, Michael O'Riordan, Ciarán Lee
Sep 25, 2026|RecSys
Bootstrapping Conversational Recommendation Agents At Spotify: Synthetic Data Generation and Self-Improvement Loops
E. Palumbo, A. Tamborrino, V. Ode, B. Lacker, A. C. Escoda, J. Hopple, M. Better, J. Leoni, H. Galvão, H. Bouchard, M. Lalmas, J. L. R. García, A. Abebe, A. Clifton, A. Blomberg, H. Lindström, D. Doro, C. D. Cardet
Sep 23, 2026|RecSys - GenAIECommerce Workshop
The Disconnect Between Better Descriptive Reasoning Trace Quality and Recommendation Effectiveness
Gustavo Penha, Juan Elenter Litwin, Claudia Hauff, Hugues Bouchard, Paul Bennett, Mounia Lalmas
Sep 23, 2026|RecSys - USRW (Unified Search & Recommendation) Workshop
From IR to RecSys: Evaluating LLM-based Judges in Cranfield-style Recommendation Collections
Gustavo Penha, Aleksandr V. Petrov, Claudia Hauff, Enrico Palumbo, Ali Vardasbi, Edoardo D'Amico, Francesco Fabbri, Alice Wang, Praveen Ravichandran, Henrik Lindström, Hugues Bouchard, Mounia Lalmas
Sep 23, 2026|RecSys
Do Sequential Recommendation Benchmarks Really Require Higher-Order Sequence Modelling?
Aleksandr V. Petrov, Praveen Ravichandran, Paul Bennett, Hugues Bouchard, Mounia Lalmas
Sep 18, 2026|RecSys
Who Are We Recommending To? Recommender Systems in the Agentic Web
Himan Abdollahpouri, Kyle Kretschman, Sai Srivatsa Ravindranath, Jackie Doremus, Mounia Lalmas
Sep 18, 2026|RecSys
Hypothesis-Driven Shelf Generation for Personalised Recommendation
Aleksandr V. Petrov, Tarun Chillara, Matthew D. Moellman, Lucas de Haas, Yabai Song, Alina Susoykina, Melissa Crawford, Gabriel Negash, Erik Franco, Tasnim Rahman, Binal Jhaveri, Shubham Bansal, Hugues Bouchard, Roberto Mirizzi, Mounia Lalmas, Aloïs Gruson
Aug 11, 2026|KDD
From Habits to Discovery: Deploying LLMs for Personalized Generative Recommendations at Spotify
Edoardo D'Amico, Marco De Nadai, Praveen Chandar et al
Aug 11, 2026|KDD
A Unified Model for Personalization: Language-Steerable Generative Recommendation, Search, and User Understanding
Marco De Nadai, Edoardo D'Amico, Paul Bennett, Mounia Lalmas, Praveen Chandar et al
Aug 7, 2026|KDD
Stochastic Primal-Dual Decoding for Multiobjective Generative Recommender Systems
Dmitrii Moor, Ben Carterette, Senthilkumar Krishnamoorthy, Kyle Kretschman, Denis Beslic, Melissa Yalla, Alice Y Wang, Mounia Lalmas
Jul 27, 2026|SIGIR
As It Was: Aligning LLM Search Evaluation with Historical User Preferences
Ali Vardasbi, Gustavo Penha, Enrico Palumbo, Claudia Hauff, Hugues Bouchard, Mounia Lalmas
Jun 16, 2026|ICLR
Measuring Uncertainty Calibration
Kamil Ciosek, Nicolò Felicioni,Sina Ghiassian, Juan Elenter, Francesco Tonolini, David Gustafsson, Eva Garcia-Martin, Carmen Gonzalez, Raphaëlle Bertrand-Lalo
Jun 16, 2026|AISTATS
A Bayesian Information Theoretic Approach to Data Attribution
Dharmesh Tailor, Kamil Ciosek, Nicolò Felicioni
Jun 16, 2026|AISTATS
A Gaussian Process View on Observation Noise and Initialization in Wide Neural Networks
Sergio Calvo-Ordoñez, Jonathan Plenk, Richard Bergna, Alvaro Cartea, Jose Miguel Hernandez-Lobato, Konstantina Palla, Kamil Ciosek
Jun 16, 2026|CHIIR
PulseSearch: Modeling Long- and Short-term Patterns for Personalized Music Search Suggestions
Antonios Anagnostou, Jose Luis Redondo Garcia, Emelie Jin, Jonathan Warburton, Vinay Rao, Yannis Kantarelis, Daniel Lazarovski, Dani Doro, Francesco Cucari, Christine Doig Cardet, Hugues Bouchard, Dominic Child, Jonathan C. Brooks-Bartlett, Mounia Lalmas
Mar 17, 2026|WSDM
Cold-Starting Podcast Ads and Promotions with Multi-Task Learning on Spotify
Shivam Verma, Hannes Karlbom, Yu Zhao, Nick Topping, Vivian Chen, Kieran Stanley, Bharath Rengarajan
Nov 13, 2025|Journal of Causal Inference
Spillover Detection for Donor Selection in Synthetic Control Models
Michael O'Riordan, Ciarán Gilligan-Lee
Nov 11, 2025|CIKM
Learning Optimal Personalised Reservation Prices in Impression Ad Auctions with Mixture Density Networks
Dmitrii Moor, Emma Zetterdahl, Paul van Vliet, Zhenwen Dai, Mounia Lalmas

Explore our publications and scientific contributions

Robust Fusion of Semantic and Behavioural Signals for LLM Reranking in Personalised Search

Intent-Description Anchoring Bias in LLM-as-a-Judge Evaluation of Recommendation Systems

Incremental Recommendation via Causal Models

Bootstrapping Conversational Recommendation Agents At Spotify: Synthetic Data Generation and Self-Improvement Loops

The Disconnect Between Better Descriptive Reasoning Trace Quality and Recommendation Effectiveness

From IR to RecSys: Evaluating LLM-based Judges in Cranfield-style Recommendation Collections

Do Sequential Recommendation Benchmarks Really Require Higher-Order Sequence Modelling?

Who Are We Recommending To? Recommender Systems in the Agentic Web

Hypothesis-Driven Shelf Generation for Personalised Recommendation

From Habits to Discovery: Deploying LLMs for Personalized Generative Recommendations at Spotify

A Unified Model for Personalization: Language-Steerable Generative Recommendation, Search, and User Understanding

Stochastic Primal-Dual Decoding for Multiobjective Generative Recommender Systems

As It Was: Aligning LLM Search Evaluation with Historical User Preferences

Measuring Uncertainty Calibration

A Bayesian Information Theoretic Approach to Data Attribution

A Gaussian Process View on Observation Noise and Initialization in Wide Neural Networks

PulseSearch: Modeling Long- and Short-term Patterns for Personalized Music Search Suggestions

Cold-Starting Podcast Ads and Promotions with Multi-Task Learning on Spotify

Spillover Detection for Donor Selection in Synthetic Control Models

Learning Optimal Personalised Reservation Prices in Impression Ad Auctions with Mixture Density Networks