| 2024 | FLIP: Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction. | Hangyu Wang, Jianghao Lin, Xiangyang Li, Bo Chen, Chenxu Zhu, Ruiming Tang, Weinan Zhang, Yong Yu |
| 2024 | What to compare? Towards understanding user sessions on price comparison platforms. | Ahmadou Wagne, Julia Neidhardt |
| 2024 | From Clicks to Carbon: The Environmental Toll of Recommender Systems. | Tobias Vente, Lukas Wegmeth, Alan Said, Joeran Beel |
| 2024 | RePlay: a Recommendation Framework for Experimentation and Production Use. | Alexey Vasilev, Anna Volodkevich, Denis Kulandin, Tatiana Bysheva, Anton Klenitskiy |
| 2024 | It's (not) all about that CTR: A Multi-Stakeholder Perspective on News Recommender Metrics. | Hanne Vandenbroucke, Annelien Smets |
| 2024 | beeFormer: Bridging the Gap Between Semantic and Interaction Similarity in Recommender Systems. | Vojtech Vancura, Pavel Kordk, Milan Straka |
| 2024 | Putting Popularity Bias Mitigation to the Test: A User-Centric Evaluation in Music Recommenders. | Robin Ungruh, Karlijn Dinnissen, Anja Volk, Maria Soledad Pera, Hanna Hauptmann |
| 2024 | Transformers Meet ACT-R: Repeat-Aware and Sequential Listening Session Recommendation. | Viet-Anh Tran, Guillaume Salha-Galvan, Bruno Massoni Sguerra, Romain Hennequin |
| 2024 | Less is More: Towards Sustainability-Aware Persuasive Explanations in Recommender Systems. | Thi Ngoc Trang Tran, Seda Polat Erdeniz, Alexander Felfernig, Sebastian Lubos, Merfat El Mansi, Viet-Man Le |
| 2024 | Leveraging Monte Carlo Tree Search for Group Recommendation. | Antonela Tommasel, J. Andres Diaz-Pace |
| 2024 | Fairness Matters: A look at LLM-generated group recommendations. | Antonela Tommasel |
| 2024 | Fair Reciprocal Recommendation in Matching Markets. | Yoji Tomita, Tomohiko Yokoyama |
| 2024 | ReLand: Integrating Large Language Models' Insights into Industrial Recommenders via a Controllable Reasoning Pool. | Changxin Tian, Binbin Hu, Chunjing Gan, Haoyu Chen, Zhuo Zhang, Li Yu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Jiawei Chen |
| 2024 | Societal Sorting as a Systemic Risk of Recommenders. | Luke Thorburn, Maria Polukarov, Carmine Ventre |
| 2024 | Explore versus repeat: insights from an online supermarket. | Mariagiorgia Agnese Tandoi, Daniela Solis Morales |
| 2024 | Comparative Analysis of Pretrained Audio Representations in Music Recommender Systems. | Yan-Martin Tamm, Anna Aljanaki |
| 2024 | User Knowledge Prompt for Sequential Recommendation. | Yuuki Tachioka |
| 2024 | Deep Recommendation using Graphs. | Panagiotis Symeonidis |
| 2024 | End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling. | Zexu Sun, Hao Yang, Dugang Liu, Yunpeng Weng, Xing Tang, Xiuqiang He |
| 2024 | AI-based Human-Centered Recommender Systems: Empirical Experiments and Research Infrastructure. | Ruixuan Sun |
| 2024 | Leveraging LightGBM Ranker for Efficient Large-Scale News Recommendation Systems. | Tetsuro Sugiura, Yosuke Yamagishi, Yodai Kishimoto |
| 2024 | Is It Really Complementary? Revisiting Behavior-based Labels for Complementary Recommendation. | Kai Sugahara, Chihiro Yamasaki, Kazushi Okamoto |
| 2024 | RPAF: A Reinforcement Prediction-Allocation Framework for Cache Allocation in Large-Scale Recommender Systems. | Shuo Su, Xiaoshuang Chen, Yao Wang, Yulin Wu, Ziqiang Zhang, Kaiqiao Zhan, Ben Wang, Kun Gai |
| 2024 | NORMalize 2024: The Second Workshop on Normative Design and Evaluation of Recommender Systems. | Alain Starke, Sanne Vrijenhoek, Lien Michiels, Johannes Kruse, Nava Tintarev |
| 2024 | On Interpretability of Linear Autoencoders. | Martin Spisk, Radek Bartyzal, Antonn Hoskovec, Ladislav Peska |