Hub Library
How to Access Recordings
Recordings will be available here in the library within 48 hours of the end of the session and be available until January 31, 2025.
"More to Read'' at the Los Angeles Times: Solving a Cold Start Problem with LLMs to Improve Story Discovery
Franklin Horn (Los Angeles Times), Aurelia Alston (Los Angeles Times), Won You (Los Angeles Times) and David Kaufman (Los Angeles Times)
Live Session
A Comparative Analysis of Text-Based Explainable Recommender Systems
Alejandro Ariza-Casabona (University of Barcelona), Ludovico Boratto (University of Cagliari) and Maria Salamo (Departament of Mathematics and Computer Science, Universitat de Barcelona)
Live Session
A Dataset for Adapting Recommender Systems to the Fashion Rental Economy
Karl Audun Borgersen (Universitetet i Agder), Morten Goodwin (University of Agder, Department of ICT), Morten Grundetjern (Universitetet i Agder) and Jivitesh Sharma (University of Agder)
Live Session
A Hybrid Multi-Agent Conversational Recommender System with LLM and Search Engine in E-commerce
Guangtao Nie (JD.com), Rong Zhi (JD.com), Xiaofan Yan (JD.com), Yufan du (JD.com), Xiangyang Zhang (JD.com), Jianwei Chen (JD.com), Mi Zhou (JD.com), Hongshen Chen (JD.com), Tianhao Li (JD.com), Sulong Xu (JD.com), Jinghe Hu (JD.com) and Ziguang Cheng (jd.com)
Live Session
A Multi-modal Modeling Framework for Cold-start Short-video Recommendation
Gaode Chen (Kuaishou Technology), Ruina Sun (Kuaishou Technology), Yuezihan Jiang (Kuaishou Technology), Jiangxia Cao (Kuaishou Technology), Qi Zhang (Kuaishou Technology), Jingjian Lin (Kuaishou Technology), Han Li (Kuaishou Technology), Kun Gai (Kuaishou Technology) and Xinghua Zhang (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China)
Live Session
A New Perspective in Health Recommendations: Integration of Human Pose Estimation
Gaetano Dibenedetto (University of Bari Aldo Moro)
Live Session
A Novel Evaluation Perspective on GNNs-based Recommender Systems through the Topology of the User-Item Graph
Daniele Malitesta (Université Paris-Saclay, CentraleSupélec, Inria), Claudio Pomo (Politecnico di Bari), Vito Walter Anelli (Politecnico di Bari), Alberto Carlo Maria Mancino (Politecnico di Bari), Tommaso Di Noia (Politecnico di Bari) and Eugenio Di Sciascio (Politecnico di Bari)
Live Session
A Pre-trained Zero-shot Sequential Recommendation Framework via Popularity Dynamics
Junting Wang (University of Illinois, Urbana-Champaign), Praneet Rathi (University of Illinois, Urbana-Champaign) and Hari Sundaram (University of Illinois, Urbana-Champaign)
Live Session
A Pre-trained Zero-shot Sequential Recommendation Framework via Popularity Dynamics
Junting Wang (University of Illinois, Urbana-Champaign), Praneet Rathi (University of Illinois, Urbana-Champaign) and Hari Sundaram (University of Illinois, Urbana-Champaign)
Live Session
A Tool for Explainable Pension Fund Recommendations using Large Language Models
Eduardo Alves Silva (Federal University of Amazonas), Leandro Balby Marinho (Federal University of Campina Grande), Edleno Silva Moura (Federal University of Amazonas) and Altigran Soares Silva (Federal University of Amazonas)
Live Session
A Unified Graph Transformer for Overcoming Isolations in Multi-modal Recommendation
Zixuan Yi (University of Glasgow) and Iadh Ounis (University of Glasgow)
Live Session
A multimodal single-branch embedding network for recommendation in cold-start and missing modality scenarios
Christian Ganhör (Johannes Kepler University Linz), Marta Moscati (Johannes Kepler University Linz), Shah Nawaz (Johannes Kepler University Linz), Anna Hausberger (Johannes Kepler University Linz) and Markus Schedl (Johannes Kepler University Linz)
Live Session
A multimodal single-branch embedding network for recommendation in cold-start and missing modality scenarios
Christian Ganhör (Johannes Kepler University Linz), Marta Moscati (Johannes Kepler University Linz), Shah Nawaz (Johannes Kepler University Linz), Anna Hausberger (Johannes Kepler University Linz) and Markus Schedl (Johannes Kepler University Linz)
Live Session
AI-assisted Coding with Cody: Lessons from Context Retrieval and Evaluation for Code Recommendations
Jan Hartman (Sourcegraph), Dominic Cooney (Sourcegraph), Rafal Gajdulewicz (Sourcegraph), Olaf Geirsson (Sourcegraph), Beyang Liu (Sourcegraph), Hitesh Sagtani (Sourcegraph), Quinn Slack (Sourcegraph), Julie Tibshirani (Sourcegraph) and Rishabh Mehrotra (Sourcegraph)
Live Session
AI-based Human-Centered Recommender Systems: Empirical Experiments and Research Infrastructure
Ruixuan Sun (University of Minnesota)
Live Session
AIE: Auction Information Enhanced Framework for CTR Prediction in Online Advertising
Yang Yang (Huawei Noah’s Ark Lab), Bo Chen (Huawei Noah’s Ark Lab), Chenxu Zhu (Huawei Noah’s Ark Lab), Menghui Zhu (Huawei Noah’s Ark Lab), Xinyi Dai (Huawei Noah Ark’s Lab), Huifeng Guo (Huawei Noah Ark’s Lab), Muyu Zhang (Huawei Noah Ark’s Lab), Zhenhua Dong (Huawei Noah Ark’s Lab) and Ruiming Tang (Huawei Noah Ark’s Lab)
Live Session
AIE: Auction Information Enhanced Framework for CTR Prediction in Online Advertising
Yang Yang (Huawei Noah’s Ark Lab), Bo Chen (Huawei Noah's Ark Lab), Chenxu Zhu (Huawei Noah’s Ark Lab), Menghui Zhu (Huawei Noah’s Ark Lab), Xinyi Dai (Huawei Noah Ark's Lab), Huifeng Guo (Huawei Noah Ark's Lab), Muyu Zhang (Huawei Noah Ark's Lab), Zhenhua Dong (Huawei Noah Ark's Lab) and Ruiming Tang (Huawei Noah Ark's Lab)
Live Session
AMBAR: A dataset for Assessing Multiple Beyond-Accuracy Recommenders
Elizabeth Gómez (Universitat de Barcelona), David Contreras (Universidad Arturo Prat), Ludovico Boratto (University of Cagliari) and Maria Salamo (Departament of Mathematics and Computer Science, Universitat de Barcelona)
Live Session
Accelerating the Surrogate Retraining for Poisoning Attacks against Recommender Systems
Yunfan Wu (Institute of Computing Technology, Chinese Academy of Sciences), Qi Cao (Institute of Computing Technology, Chinese Academy of Sciences), Shuchang Tao (Institute of Computing Technology, Chinese Academy of Sciences), Kaike Zhang (Institute of Computing Technology, Chinese Academy of Sciences), Fei Sun (Institute of Computing Technology, Chinese Academy of Sciences) and Huawei Shen (Institute of Computing Technology, Chinese Academy of Sciences)
Live Session
Adaptive Fusion of Multi-View for Graph Contrastive Recommendation
Mengduo Yang (zhejiang university), Yi Yuan (zhejiang university), Jie Zhou (zhejiang university), Meng Xi (zhejiang university), Xiaohua Pan (zhejiang university), Ying Li (zhejiang university), Yangyang Wu (zhejiang university), Jinshan Zhang (zhejiang university) and Jianwei Yin (zhejiang university)
Live Session
Analyzing User Preferences and Quality Improvement on Bing's WebPage Recommendation Experience with Large Language Models
Jaidev Shah (Microsoft AI), Gang Luo (Microsoft), Jialin Liu (Microsoft AI), Amey Barapatre (Microsoft AI), Fan Wu (Microsoft AI), Chuck Wang (Microsoft AI) and Hongzhi Li (Microsoft)
Live Session
Are We Explaining Flawed Recommenders? Incorporating Recommender Performance for Evaluating Explainers
Amir Reza Mohammadi (University of Innsbruck), Andreas Peintner (University of Innsbruck), Michael Müller (University of Innsbruck) and Eva Zangerle (University of Innsbruck)
Live Session
Assessing the Impact of Music Recommendation Diversity on Listeners: A Longitudinal Study
Lorenzo Porcaro, Emilia Gómez, Carlos Castillo
Live Session
Balancing Habit Repetition and New Activity Exploration: A Longitudinal Micro-Randomized Trial in Physical Activity Recommendations
Ine Coppens (WAVES - imec - Ghent University), Toon De Pessemier (WAVES - imec - Ghent University) and Luc Martens (WAVES - imec - Ghent University)
Live Session
Bayesian Optimization with LLM-Based Acquisition Functions for Natural Language Preference Elicitation
David Austin (University of Waterloo), Anton Korikov (University of Toronto), Armin Toroghi (University of Toronto) and Scott Sanner (University of Toronto)
Live Session
Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations
Anima Singh (Google DeepMind), Trung Vu (Google), Nikhil Mehta (Google DeepMind), Raghunandan Keshavan (Google), Maheswaran Sathiamoorthy (Google DeepMind), Yilin Zheng (Google), Lichan Hong (Google DeepMind), Lukasz Heldt (Google), Li Wei (Google), Devansh Tandon (Google), Ed Chi (Google DeepMind) and Xinyang Yi (Google DeepMind)
Live Session
Bias in Book Recommendation
Savvina Daniil (CWI)
Live Session
Biased User History Synthesis for Personalized Long-Tail Item Recommendation
Keshav Balasubramanian (University of Southern California), Abdulla Alshabanah (University of Southern California), Elan Markowitz (Information Sciences Institute at the University of Southern California), Greg Ver Steeg (University of California Riverside) and Murali Annavaram (University of Southern California)
Live Session
Bootstrapping Conditional Retrieval for User-to-Item Recommendations
Hongtao Lin (Pinterest), Haoyu Chen (Pinterest), Jaewon Yang (Pinterest) and Jiajing Xu (Pin)
Live Session
Bridging Search and Recommendation in Generative Retrieval: Does One Task Help the Other?
Gustavo Penha (Spotify), Ali Vardasbi (Spotify), Enrico Palumbo (Spotify), Marco De Nadai (Spotify) and Hugues Bouchard (Spotify)
Live Session
Bridging Viewpoints in News with Recommender Systems
Jia Hua Jeng (MediaFutures, University of Bergen)
Live Session
Bridging the Gap: Unpacking the Hidden Challenges in Knowledge Distillation for Online Ranking Systems
Nikhil Khani (Google LLC), Li Wei (Google LLC), Aniruddh Nath (Google LLC), Shawn Andrews (Google LLC), Shuo Yang (Google LLC), Yang Liu (Google LLC) and Pendo Abbo (Google LLC)
Live Session
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis
Jonathan Stray, Alon Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Chloe Bakalar, Lex Beattie, Michael Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, Nina Vasan
Live Session
CALRec: Contrastive Alignment of Generative LLMs For Sequential Recommendation
Yaoyiran Li (University of Cambridge), Xiang Zhai (Google), Moustafa Alzantot (Google), Keyi Yu (Google), Ivan Vulić (University of Cambridge), Anna Korhonen (University of Cambridge) and Mohamed Hammad (Google)
Live Session
CALRec: Contrastive Alignment of Generative LLMs For Sequential Recommendation
Yaoyiran Li (University of Cambridge), Xiang Zhai (Google), Moustafa Alzantot (Google), Keyi Yu (Google), Ivan Vulić (University of Cambridge), Anna Korhonen (University of Cambridge) and Mohamed Hammad (Google)
Live Session
CAPRI-FAIR: Integration of Multi-sided Fairness in Contextual POI Recommendation Framework
Francis Dela Cruz (University of New South Wales), Flora D. Salim (University of New South Wales), Yonchanok Khaokaew (University of New South Wales) and Jeffrey Chan (RMIT University)
Live Session
CEERS: Counterfactual Evaluations of Explanations in Recommender Systems
Mikhail Baklanov (Tel Aviv University)
Live Session
CRS-Que: A User-centric Evaluation Framework for Conversational Recommender Systems
Yucheng Jin, Li Chen, Wanling Cai, Xianglin Zhao
Live Session
Calibrating the Predictions for Top-N Recommendations
Masahiro Sato (FUJIFILM)
Live Session
Can editorial decisions impair journal recommendations? Analysing the impact of journal characteristics on recommendation systems
Elias Entrup (TIB Leibniz Information Centre for Science and Technology), Ralph Ewerth (TIB Leibniz Information Centre for Science and Technology, L3S Research Center, Leibniz Universität Hannover) and Anett Hoppe (TIB Leibniz Information Centre for Science and Technology, L3S Research Centre, Leibniz Universität Hannover)
Live Session
Co-optimize Content Generation and Consumption in a Large Scale Video Recommendation System
Zhen Zhang (Google Inc.), Qingyun Liu (Google Inc.), Yuening Li (Google Inc.), Sourabh Bansod (Google Inc.), Mingyan Gao (Google Inc.), Yaping Zhang (Google Inc.), Shuchao Bi (Google Inc.) and Liang Liu (Google Inc.)
Live Session
CoST: Contrastive Quantization based Semantic Tokenization for Generative Recommendation
Jieming Zhu (Huawei Noah's Ark Lab), Mengqun Jin (Shenzhen International Graduate School, Tsinghua University), Qijiong Liu (The Hong Kong Polytechnic University), Zexuan Qiu (The Chinese University of Hong Kong), Zhenhua Dong (Huawei Noah's Ark Lab) and Xiu Li (Shenzhen International Graduate School, Tsinghua University)
Live Session
Comparative Analysis of Pretrained Audio Representations in Music Recommender Systems
Yan-Martin Tamm (University of Tartu) and Anna Aljanaki (University of Tartu)
Live Session
ConFit: Improving Resume-Job Matching using Data Augmentation and Contrastive Learning
Xiao Yu (Columbia University), Jinzhong Zhang (Intellipro) and Zhou Yu (Columbia University)
Live Session
ConFit: Improving Resume-Job Matching using Data Augmentation and Contrastive Learning
Xiao Yu (Columbia University), Jinzhong Zhang (Intellipro) and Zhou Yu (Columbia University)
Live Session
Context-based Entity Recommendation for Knowledge Workers: Establishing a Benchmark on Real-life Data
Mahta Bakhshizadeh (German Research Center for Artificial Intelligence (DFKI)), Heiko Maus (German Research Center for Artificial Intelligence (DFKI)) and Andreas Dengel (German Research Center for Artificial Intelligence (DFKI))
Live Session
Country-diverted experiments for mitigation of network effects
Lina Lin (Google), Changping Meng (Google), Jennifer Brennan (Google Research), Jean Pouget-Abadie (Google Research), Ningren Han (Google), Shuchao Bi (Google) and Yajun Peng (Google)
Live Session
Cross-Domain Latent Factors Sharing via Implicit Matrix Factorization
Abdulaziz Samra (Skoltech), Evgeny Frolov (AIRI Labs, Skoltech), Alexey Vasilev (Sber, AI Lab), Alexander Grigorevskiy (Comparables.ai) and Anton Vakhrushev (Sber, AI Lab)
Live Session
DNS-Rec: Data-aware Neural Architecture Search for Recommender Systems
Sheng Zhang (City University of Hong Kong), Maolin Wang (City University of Hong Kong), Xiangyu Zhao (City University of Hong Kong), Ruocheng Guo (ByteDance Research), Yao Zhao (Ant Group), Chenyi Zhuang (Ant Group), Jinjie Gu (Ant Group), Zijian Zhang (Jilin University) and Hongzhi Yin (The University of Queensland)
Live Session
DNS-Rec: Data-aware Neural Architecture Search for Recommender Systems
Sheng Zhang (City University of Hong Kong), Maolin Wang (City University of Hong Kong), Xiangyu Zhao (City University of Hong Kong), Ruocheng Guo (ByteDance Research), Yao Zhao (Ant Group), Chenyi Zhuang (Ant Group), Jinjie Gu (Ant Group), Zijian Zhang (Jilin University) and Hongzhi Yin (The University of Queensland)
Live Session
Data Augmentation using Reverse Prompt for Cost-Efficient Cold-Start Recommendation
Genki Kusano (NEC)
Live Session
Democratizing Urban Mobility Through an Open-Source, Multi-Criteria Route Recommendation System
Alexander Eggerth (ETH Zurich), Javier Argota Sánchez-Vaquerizo (ETH Zurich), Dirk Helbing (ETH Zurich) and Sachit Mahajan (ETH Zurich)
Live Session
Discerning Canonical User Representation for Cross-Domain Recommendation
Siqian Zhao (University at Albany – SUNY) and Sherry Sahebi (University at Albany – SUNY)
Live Session
Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Models
Yu Cui (Zhejiang University), Feng Liu (OPPO Co Ltd), Pengbo Wang (University of Electronic Science and Technology of China), Bohao Wang (Zhejiang University), Heng Tang (Zhejiang University), Yi Wan (OPPO Co Ltd), Jun Wang (OPPO Co Ltd) and Jiawei Chen (Zhejiang University)
Live Session
Do Not Wait: Learning Re-Ranking Model Without User Feedback At Serving Time in E-Commerce
Yuan Wang (Alibaba Group), Zhiyu Li (Alibaba Group), Changshuo Zhang (Gaoling School of Artificial Intelligence, Renmin University of China), Sirui Chen (School of Information, Renmin University of China), Xiao Zhang (Gaoling School of Artificial Intelligence, Renmin University of China), Jun Xu (Gaoling School of Artificial Intelligence, Renmin University of China) and Quan Lin (Alibaba Group)
Live Session
Do Recommender Systems Promote Local Music? A Reproducibility Study Using Music Streaming Data
Kristina Matrosova (Deezer Research, CNRS, Geographie-Cités), Lilian Marey (Deezer Research, LTCI, Télécom Paris), Guillaume Salha-Galvan (Deezer Research), Thomas Louail (CNRS, Geographie-Cités), Olivier Bodini (LIPN, Université Sorbonne Paris Nord) and Manuel Moussallam (Deezer Research)
Live Session
Does It Look Sequential? An Analysis of Datasets for Evaluation of Sequential Recommendations
Anton Klenitskiy (Sber AI Lab), Anna Volodkevich (Sber AI Lab), Anton Pembek (Sber AI Lab, Lomonosov Moscow State University (MSU)) and Alexey Vasilev (Sber AI Lab)
Live Session
Dynamic Product Image Generation and Recommendation at Scale for Personalized E-commerce
Ádám Tibor Czapp (Taboola Budapest), Mátyás Jani (Taboola Budapest), Bálint Domián (Taboola Budapest) and Balázs Hidasi (Taboola Budapest)
Live Session
Dynamic Stage-aware User Interest Learning for Heterogeneous Sequential Recommendation
Weixin Li (Shenzhen University), Xiaolin Lin (Shenzhen University), Weike Pan (Shenzhen University) and Zhong Ming (Shenzhen University)
Live Session
Effective Off-Policy Evaluation and Learning in Contextual Combinatorial Bandits
Tatsuhiro Shimizu (Independent Researcher), Koichi Tanaka (Keio Univercity), Ren Kishimoto (Tokyo Institute of Technology), Haruka Kiyohara (Cornell University), Masahiro Nomura (CyberAgent, Inc.) and Yuta Saito (Cornell University)
Live Session
Efficient Inference of Sub-Item Id-based Sequential Recommendation Models with Millions of Items
Aleksandr Petrov (University of Glasgow), Craig Macdonald (University of Glasgow) and Nicola Tonellotto (University of Pisa)
Live Session
EmbSum: Leveraging the Summarization Capabilities of Large Language Models for Content-Based Recommendations
Chiyu Zhang (University of British Columbia), Yifei Sun (Meta), Minghao Wu (Monash University), Jun Chen (Meta), Jie Lei (Meta), Muhammad Abdul-Mageed (The University of British Columbia), Rong Jin (Meta), Angli Liu (Meta), Ji Zhu (Meta), Sem Park (Meta), Ning Yao (Meta) and Bo Long (Meta)
Live Session
Embedding Optimization for Training Large-scale Deep Learning Recommendation Systems with EMBark
Shijie Liu (NVIDIA), Nan Zheng (NVIDIA), Hui Kang (NVIDIA), Xavier Simmons (NVIDIA), Junjie Zhang (NVIDIA), Matthias Langer (NVIDIA), Wenjing Zhu (NVIDIA), Minseok Lee (NVIDIA) and Zehuan Wang (NVIDIA)
Live Session
Embedding Optimization for Training Large-scale Deep Learning Recommendation Systems with EMBark
Shijie Liu (NVIDIA), Nan Zheng (NVIDIA), Hui Kang (NVIDIA), Xavier Simmons (NVIDIA), Junjie Zhang (NVIDIA), Matthias Langer (NVIDIA), Wenjing Zhu (NVIDIA), Minseok Lee (NVIDIA) and Zehuan Wang (NVIDIA)
Live Session
Embedding based retrieval for long tail search queries in ecommerce
Akshay Kekuda (Best Buy), Yuyang Zhang (Best Buy) and Arun Udayashankar (Best Buy)
Live Session
Encouraging Exploration in Spotify Search through Query Recommendations
Henrik Lindstrom (Spotify), Humberto Jesús Corona Pampín (Spotify), Enrico Palumbo (Spotify) and Alva Liu (Spotify)
Live Session
End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling
Zexu Sun (Renmin University of China), Hao Yang (Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China), Dugang Liu (Shenzhen University), Yunpeng Weng (Tencent), Xing Tang (Tencent) and Xiuqiang He (FiT,Tencent)
Live Session
Enhancing Cross-Domain Recommender Systems with LLMs: Evaluating Bias and Beyond-Accuracy Measures
Thomas Elmar Kolb (TU Wien)
Live Session
Enhancing Performance and Scalability of Large-Scale Recommendation Systems with Jagged Flash Attention
Rengan Xu (Meta), Junjie Yang (Meta), Yifan Xu (Meta), Hong Li (Meta), Xing Liu (Meta), Devashish Shankar (Meta), Haoci Zhang (Meta), Meng Liu (Meta), Boyang Li (Meta), Yuxi Hu (Meta), Mingwei Tang (Meta), Zehua Zhang (Meta), Tunhou Zhang (Meta), Dai Li (Meta), Sijia Chen (Meta), Jiaqi Zhai (Meta), Bill Zhu (Meta), Arnold Overwijk (Meta) and Sri Reddy (Meta)
Live Session
Enhancing Privacy in Recommender Systems through Differential Privacy Techniques
Angela Di Fazio (Politecnico di Bari)
Live Session
Enhancing Recommendation Quality of the SASRec Model by Mitigating Popularity Bias
Venkata Harshit Koneru (ZDF), Xenija Neufeld (Accso – Accelerated Solutions GmbH), Sebastian Loth (ZDF) and Andreas Grün (ZDF)
Live Session
Enhancing Sequential Music Recommendation with Negative Feedback-informed Contrastive Learning
Pavan Seshadri (Georgia Institute of Technology), Shahrzad Shashaani (Vienna University of Technology) and Peter Knees (Vienna University of Technology)
Live Session
Enhancing Sequential Music Recommendation with Personalized Popularity Awareness
Davide Abbattista (Politecnico di Bari), Vito Walter Anelli (Politecnico di Bari), Tommaso Di Noia (Politecnico di Bari), Craig Macdonald (University of Glasgow) and Aleksandr Petrov (University of Glasgow)
Live Session
Entity-Aware Collections Ranking: A Joint Scoring Approach
Sihao Chen (Shopee Pte. Ltd.), Sheng Li (Shopee Pte. Ltd.), Youhe Chen (Shopee Pte. Ltd.) and Dong Yang (Shopee Pte. Ltd.)
Live Session
Evaluating the Pros and Cons of Recommender Systems Explanations
Kathrin Wardatzky (University of Zurich)
Live Session
Evaluation Measures of Individual Item Fairness for Recommender Systems: A Critical Study
Theresia Veronika Rampisela, Maria Maistro, Tuukka Ruotsalo, and Christina Lioma
Live Session
Evaluation and simplification of text difficulty using LLMs in the context of recommending texts in French to facilitate language learning
Henri Jamet (Faculty of Business and Economics, University of Lausanne), Maxime Manderlier (Faculty of Engineering, University of Mons (UMONS)), Yash Raj Shrestha (Faculty of Business and Economics, University of Lausanne) and Michalis Vlachos (Faculty of Business and Economics, University of Lausanne)
Live Session
Explainability in Music Recommender System
Shahrzad Shashaani (TU Wien)
Live Session
Explainable Multi-Stakeholder Job Recommender Systems
Roan Schellingerhout (Maastricht University)
Live Session
Explainable and Faithful Educational Recommendations through Causal Language Modelling via Knowledge Graphs
Neda Afreen (University of Cagliari)
Live Session
Exploratory Analysis of Recommending Urban Parks for Health-Promoting Activities
Linus W. Dietz (King's College London), Sanja Šćepanović (Nokia Bell Labs), Ke Zhou (Nokia Bell Labs) and Daniele Quercia (Nokia Bell Labs)
Live Session
Explore versus repeat: insights from an online supermarket
Mariagiorgia Agnese Tandoi (Picnic Technologies) and Daniela Solis Morales (Picnic Technologies)
Live Session
Exploring Coresets for Efficient Training and Consistent Evaluation of Recommender Systems
Zheng Ju (Insight Centre for Data Analytics), Honghui Du (University College Dublin), Elias Tragos (Insight Centre for Data Analytics), Neil Hurley (University College Dublin) and Aonghus Lawlor (University College Dublin)
Live Session
Exploring the Landscape of Recommender Systems Evaluation: Practices and Perspectives
Christine Bauer, Eva Zangerle, Alan Said
Live Session
FLIP: Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction
Hangyu Wang (Shanghai Jiao Tong University), Jianghao Lin (Shanghai Jiao Tong University), Xiangyang Li (Huawei Noah’s Ark Lab), Bo Chen (Huawei Noah’s Ark Lab), Chenxu Zhu (Huawei Noah’s Ark Lab), Ruiming Tang (Huawei Noah’s Ark Lab), Weinan Zhang (Shanghai Jiao Tong University) and Yong Yu (Shanghai Jiao Tong University)
Live Session
Fair Augmentation for Graph Collaborative Filtering
Ludovico Boratto (University of Cagliari), Francesco Fabbri (Spotify), Gianni Fenu (University of Cagliari), Mirko Marras (University of Cagliari) and Giacomo Medda (University of Cagliari)
Live Session
Fair Reciprocal Recommendation in Matching Markets
Yoji Tomita (CyberAgent, Inc.) and Tomohiko Yokoyama (The University of Tokyo)
Live Session
FairCRS: Towards User-oriented Fairness in Conversational Recommendation Systems
Qin Liu (Jinan University), Xuan Feng (Jinan University), Tianlong Gu (Jinan University) and Xiaoli Liu (Jinan University)
Live Session
FairCRS: Towards User-oriented Fairness in Conversational Recommendation Systems
Qin Liu (Jinan University), Xuan Feng (Jinan University), Tianlong Gu (Jinan University) and Xiaoli Liu (Jinan University)
Live Session
Fairness Matters: A look at LLM-generated group recommendations
Antonela Tommasel (ISISTAN Research Institute, CONICET-UNCPBA)
Live Session
Fairness and Transparency in Music Recommender Systems: Improvements for Artists
Karlijn Dinnissen (Utrecht University)
Live Session
Fairness explanation in recommender systems
Luan Souza (University of São Paulo)
Live Session
FedLoCA: Low-Rank Coordinated Adaptation with Knowledge Decoupling for Federated Recommendations
Yuchen Ding (University of Science and Technology of China), Siqing Zhang (University of Science and Technology of China), Boyu Fan (University of Helsinki), Wei Sun (University of Science and Technology of China), Yong Liao (University of Science and Technology of China) and Pengyuan Zhou (Aarhus University)
Live Session
From Clicks to Carbon: The Environmental Toll of Recommender Systems
Tobias Vente (University of Siegen), Lukas Wegmeth (University of Siegen), Alan Said (University of Gothenburg) and Joeran Beel (University of Siegen)
Live Session
GLAMOR: Graph-based LAnguage MOdel embedding for citation Recommendation
Zafar Ali (School of Computer Science and Engineering, Southeast University, Nanjing 210096, China), Guilin Qi (School of Computer Science and Engineering, Southeast University, Nanjing 210096, China), Irfan Ullah (Department of Computer Science, Shaheed Benazir Bhutto University, Sheringal, Pakistan), Adam A. Q. Mohammed (School of Computer Science and Engineering, Southeast University, Nanjing 210096, China), Pavlos Kefalas (Department of Informatics, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece) and Khan Muhammad (Department of Applied Artificial Intelligence, School of Convergence, Sungkyunkwan University, South Korea)
Live Session
GenUI(ne) CRS: UI Elements and Retrieval-Augmented Generation in Conversational Recommender Systems with LLMs
Ulysse Maes (imec-SMIT, Vrije Universiteit Brussel), Lien Michiels (imec-SMIT, Vrije Universiteit Brussel) and Annelien Smets (imec-SMIT, Vrije Universiteit Brussel)
Live Session
How to Evaluate Serendipity in Recommender Systems: the Need for a Serendiptionnaire
Brett Binst (imec-SMIT, Vrije Universiteit Brussel)
Live Session
Improving Adversarial Robustness for Recommendation Model via Cross-Domain Distributional Adversarial Training
Jingyu Chen (Sichuan University), Lilin Zhang (Sichuan University) and Ning Yang (Sichuan University)
Live Session
Improving Data Efficiency for Recommenders and LLMs
Noveen Sachdeva (Google DeepMind), Benjamin Coleman (Google DeepMind), Wang-Cheng Kang (Google DeepMind), Jianmo Ni (Google DeepMind), James Caverlee (Texas A&M University), Lichan Hong (Google DeepMind), Ed Chi (Google DeepMind) and Derek Cheng (Google DeepMind)
Live Session
Improving the Shortest Plank: Vulnerability-Aware Adversarial Training for Robust Recommender System
Kaike Zhang (Institute of Computing Technology, CAS), Qi Cao (Institute of Computing Technology, CAS), Yunfan Wu (Institute of Computing Technology, CAS), Fei Sun (Institute of Computing Technology, CAS), Huawei Shen (Institute of Computing Technology, CAS) and Xueqi Cheng (Institute of Computing Technology, CAS)
Live Session
Information-Controllable Graph Contrastive Learning for Recommendation
Zirui Guo (Beijing University of Posts and Telecommunications), Yanhua Yu (Beijing University of Posts and Telecommunications), Yuling Wang (Beijing University of Posts and Telecommunications), Kangkang Lu (Beijing University Of Posts and Telecommunications), Zixuan Yang (Beijing University Of Posts and Telecommunications), Liang Pang (Institute of Computing Technology, Chinese Academy of Sciences) and Tat-Seng Chua (National University of Singapore)
Live Session
Informed Dataset-Selection with Algorithm-Performance-Spaces
Joeran Beel (University of Siegen), Lukas Wegmeth (University of Siegen), Lien Michiels (University of Antwerp) and Steffen Schulz (University of Siegen)
Live Session
Informfully - Research Platform for Reproducible User Studies
Lucien Heitz (University of Zurich), Julian A. Croci (University of Zurich), Madhav Sachdeva (University of Zurich) and Abraham Bernstein (University of Zurich)
Live Session
Instructing and Prompting Large Language Models for Explainable Cross-domain Recommendations
Alessandro Petruzzelli (University of Bari Aldo Moro), Cataldo Musto (University of Bari Aldo Moro), Lucrezia Laraspata (University of Bari Aldo Moro), Ivan Rinaldi (University of Bari Aldo Moro), Marco de Gemmis (University of Bari Aldo Moro), Pasquale Lops (University of Bari Aldo Moro) and Giovanni Semeraro (University of Bari Aldo Moro)
Live Session
Integrating Matrix Factorization with Graph based Models
Rachana Mehta (Pandit Deendayal Energy University)
Live Session
Interactive Content Diversity and User Exploration in Online Movie Recommenders: A Field Experiment
Ruixuan Sun, Avinash Akella, Ruoyan Kong, Moyan Zhou, and Joseph Konstan
Live Session
Is It Really Complementary? Revisiting Behavior-based Labels for Complementary Recommendation
Kai Sugahara (The University of Electro-Communications), Chihiro Yamasaki (The University of Electro-Communications) and Kazushi Okamoto (The University of Electro-Communications)
Live Session
It's (not) all about that CTR: A Multi-Stakeholder Perspective on News Recommender Metrics
Hanne Vandenbroucke (imec-SMIT Vrije Universiteit Brussel) and Annelien Smets (imec-SMIT Vrije Universiteit Brussel)
Live Session
It's Not You, It's Me: The Impact of Choice Models and Ranking Strategies on Gender Imbalance in Music Recommendation
Andres Ferraro (Pandora/SiriusXM), Michael Ekstrand (Drexel University) and Christine Bauer (Paris Lodron University Salzburg)
Live Session
Joint Modeling of Search and Recommendations Via an Unified Contextual Recommender (UniCoRn)
Moumita Bhattacharya (Netflix), Vito Ostuni (Netflix) and Sudarshan Lamkhede (Netflix)
Live Session
KGGLM: A Generative Language Model for Generalizable Knowledge Graph Representation in Recommendation
Giacomo Balloccu (University of Cagliari), Ludovico Boratto (University of Cagliari), Gianni Fenu (University of Cagliari), Mirko Marras (University of Cagliari) and Alessandro Soccol (University of Cagliari)
Live Session
Keynote: A Collectivist Vision of AI: Collaborative Learning, Statistical Incentives, and Social Welfare with Michael I. Jordan
Live Session
Keynote: The Power of AI in Recommender and Search Systems: An Industry Perspective Through the Lens of Spotify with Mounia Lalmas
Mounia Lalmas
Live Session
Keynote: Toward Human-Centered Explainable AI with Mark Riedl
Mark Riedl
Live Session
Knowledge-Enhanced Multi-Behaviour Contrastive Learning for Effective Recommendation
Zeyuan Meng (University of Glasgow), Zixuan Yi (University of Glasgow) and Iadh Ounis (University of Glasgow)
Live Session
LARR: Large Language Model Aided Real-time Scene Recommendation with Semantic Understanding
Zhizhong Wan (Meituan), Bin Yin (Meituan), Junjie Xie (Meituan), Fei Jiang (Meituan), Xiang Li (Meituan) and Wei Lin (Meituan)
Live Session
LARR: Large Language Model Aided Real-time Scene Recommendation with Semantic Understanding
Zhizhong Wan (Meituan), Bin Yin (Meituan), Junjie Xie (Meituan), Fei Jiang (Meituan), Xiang Li (Meituan) and Wei Lin (Meituan)
Live Session
LLMs for User Interest Exploration in Large-scale Recommendation Systems
Jianling Wang (Google), Haokai Lu (Google), Yifan Liu (Google), He Ma (Google), Yueqi Wang (Google), Yang Gu (Google), Shuzhou Zhang (Google), Ningren Han (Google), Shuchao Bi (Google), Lexi Baugher (Google), Ed H. Chi (Google) and Minmin Chen (Google)
Live Session
Large Language Models as Evaluators for Recommendation Explanations
Xiaoyu Zhang (Tsinghua University), Yishan Li (Tsinghua University), Jiayin Wang (Tsinghua Univeristy), Bowen Sun (Tsinghua Univeristy), Weizhi Ma (Tsinghua University), Peijie Sun (Hefei University of Technology, School of Computer and Information) and Min Zhang (Tsinghua University)
Live Session
Learned Ranking Function: From Short-term Behavior Predictions to Long-term User Satisfaction
Yi Wu (Google), Daryl Chang (Google), Jennifer She (Google), Zhe Zhao (Google), Li Wei (Google) and Lukasz Heldt (Google)
Live Session
Learning Personalized Health Recommendations via Offline Reinforcement Learning
Larry Preuett (University of Washington)
Live Session
Less is More: Towards Sustainability-Aware Persuasive Explanations in Recommender Systems
Trang Tran (Institute of Software Technology, Graz University of Technology), Seda Polat Erdeniz (Institute of Software Technology, Graz University of Technology), Alexander Felfernig (Institute of Software Technology, Graz University of Technology),Sebastian Lubos (Institute of Software Technology, Graz University of Technology), Merfat Elmansi (Institute of Software Technology, Graz University of Technology) and Viet-Man Le (Institute of Software Technology, Graz University of Technology)
Live Session
Leveraging LLM generated labels to reduce bad matches in job recommendations
Yingchi Pei (Indeed.com), Yi Wei Pang (Indeed.com), Nilanjan Sengupta (Indeed.com) and Dheeraj Toshniwal (Indeed.com)
Live Session
Leveraging Monte Carlo Tree Search for Group Recommendation
Antonela Tommasel (ISISTAN Research Institute, UNICEN University) and J. Andres Diaz-Pace (ISISTAN Research Institute, UNICEN University)
Live Session
Low Rank Field-Weighted Factorization Machines for Low Latency Item Recommendation
Alex Shtoff (Yahoo Research), Michael Viderman (Yahoo Research), Naama Haramaty-Krasne (No affiliation), Oren Somekh (Yahoo Research), Ariel Raviv (No affiliation) and Tularam Ban (Yahoo Research)
Live Session
LyricLure: Mining Catchy Hooks in Song Lyrics to Enhance Music Discovery and Recommendation
Siddharth Sharma (Amazon Inc.), Akshay Shukla (Amazon Inc.), Ajinkya Walimbe (Amazon Inc), Tarun Sharma (Amazon Inc) and Joaquin Delgado (Amazon)
Live Session
MARec: Metadata Alignment for cold-start Recommendation
ulien Monteil (Amazon Machine Learning), Volodymyr Vaskovych (Amazon Machine Learning), Wentao Lu (Amazon Machine Learning), Anirban Majumder (Amazon Machine Learning) and Anton van den Hengel (University of Adelaide)
Live Session
MAWI Rec: Leveraging Severe Weather Data in Recommendation
Brendan Duncan (UC San Diego), Surya Kallumadi (Lowe's), Taylor Berg-Kirkpatrick (UC San Diego) and Julian Mcauley (University of California San Diego)
Live Session
MLoRA: Multi-Domain Low-Rank Adaptive Network for CTR Prediction
Zhiming Yang (Northwestern Polytechnical University), Haining Gao (Alibaba Group), Dehong Gao (Northwestern Polytechnical University), Luwei Yang (Alibaba Group), Libin Yang (Northwestern Polytechnical University), Xiaoyan Cai (Northwestern Polytechnical University), Wei Ning (Alibaba Group) and Guannan Zhang (Alibaba Group)
Live Session
MMGCL: Meta Knowledge-Enhanced Multi-view Graph Contrastive Learning for Recommendations
Yuezihan Jiang (Kuaishou Technology), Changyu Li (Kuaishou Technology), Gaode Chen (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Peiyi Li (Kuaishou Technology), Qi Zhang (Kuaishou Technology), Jingjian Lin (Kuaishou Technology), Peng Jiang (Kuaishou Inc.), Fei Sun (Chinese Academy of Sciences, Beijing, China) and Wentao Zhang (Peking University)
Live Session
MODEM: Decoupling User Behavior for Shared-Account Video Recommendations on Large Screen Devices
Jiang Li (University of Science and Technology of China), Zhen Zhang (Kuaishou Technology Co., Ltd.), Xiang Feng (Kuaishou Technology Co., Ltd.), Muyang Li (Kuaishou Technology Co., Ltd.), Yongqi Liu (Kuaishou Technology Co., Ltd.) and Lantao Hu (Kuaishou Technology Co., Ltd.)
Live Session
Multi-Behavioral Sequential Recommendation
Shereen Elsayed (University of Hildesheim), Ahmed Rashed (Volkswagen Financial Services) and Lars Schmidt-Thieme (University of Hildesheim)
Live Session
Multi-Objective Recommendation via Multivariate Policy Learning
Olivier Jeunen (ShareChat), Jatin Mandav (ShareChat), Ivan Potapov (ShareChat), Nakul Agarwal (ShareChat), Sourabh Vaid (ShareChat), Wenzhe Shi (ShareChat) and Aleksei Ustimenko (ShareChat)
Live Session
Multi-Preview Recommendation via Reinforcement Learning
Yang Xu (North Carolina State University), Kuan-Ting Lai (Microsoft), Peter Xiong (Microsoft) and Zhong Wu (Microsoft)
Live Session
Multimodal Representation Learning for high-quality Recommendations in Cold-start and Beyond-Accuracy
Marta Moscati (Johannes Kepler University Linz)
Live Session
Neighborhood-Based Collaborative Filtering for Conversational Recommendation
Zhouhang Xie (University of California, San Diego), Junda Wu (University of California, San Diego), Hyunsik Jeon (University of California, San Diego), Zhankui He (University of California, San Diego), Harald Steck (Netflix Inc.), Rahul Jha (Netflix Inc.), Dawen Liang (Netflix Inc.), Nathan Kallus (Netflix Inc. & Cornell University) and Julian Mcauley (University of California San Diego)
Live Session
Not All Videos Become Outdated: Short-Video Recommendation by Learning to Deconfound Release Interval Bias
Lulu Dong (East China Normal University), Guoxiu He (East China Normal University) and Aixin Sun (Nanyang Technological University)
Live Session
Off-Policy Selection for Optimizing Ad Display Timing in Mobile Games (Samsung Instant Plays)
Katarzyna Siudek-Tkaczuk (Samsung R&D Institute Poland), Sławomir Kapka (Samsung R&D Institute Poland), Jędrzej Alchimowicz (Samsung R&D Institute Poland), Bartłomiej Swoboda (Samsung R&D Institute Poland) and Michał Romaniuk (Samsung R&D Institute Poland)
Live Session
Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems
Oleg Lesota (Johannes Kepler University Linz and Linz Institute of Technology), Jonas Geiger (Johannes Kepler University Linz and Linz Institute of Technology), Max Walder (Johannes Kepler University Linz and Linz Institute of Technology), Dominik Kowald (Know-Center GmbH and TU Graz) and Markus Schedl (Johannes Kepler University Linz and Linz Institute of Technology)
Live Session
On Interpretability of Linear Autoencoders
Martin Spišák (GLAMI.cz), Radek Bartyzal (GLAMI.cz), Antonín Hoskovec (GLAMI.cz and Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague) and Ladislav Peska (Faculty of Mathematics and Physics, Charles University, Prague, Czechia)
Live Session
One-class Matrix Factorization: Point-Wise Regression-Based or Pair-Wise Ranking-Based?
Sheng-Wei Chen (National Taiwan University) and Chih-Jen Lin (National TaiwanUniv)
Live Session
One-class recommendation systems with the hinge pairwise distance loss and orthogonal representations
Ramin Raziperchikolaei (Rakuten Institute of Technology, Rakuten Inc.) and Young-joo Chung (Rakuten institute of technology)
Live Session
Optimal Baseline Corrections for Off-Policy Contextual Bandits
Shashank Gupta (University of Amsterdam, The Netherlands), Olivier Jeunen (ShareChat), Harrie Oosterhuis (Radboud University) and Maarten de Rijke (University of Amsterdam)
Live Session
Optimizing for Participation in Recommender System
Yuan Shao (Google), Bibang Liu (Google), Sourabh Bansod (Google), Arnab Bhadury (Google), Mingyan Gao (Google) and Yaping Zhang (Google)
Live Session
Pareto Front Approximation for Multi-Objective Session-Based Recommender Systems
Timo Wilm (OTTO (GmbH & Co KG)), Philipp Normann (OTTO (GmbH & Co KG)) and Felix Stepprath (OTTO (GmbH & Co KG))
Live Session
Pay Attention to Attention for Sequential Recommendation
Yuli Liu (ANU), Min Liu (Qinghai University) and Xiaojing Liu (Qinghai University)
Live Session
Personal Values and Community-Centric Environmental Recommender Systems: enhancing Sustainability through User Engagement
Bianca Maria Deconcini (University of Turin)
Live Session
Playlist Search Reinvented: LLMs Behind the Curtain
Geetha Aluri (Amazon), Siddharth Sharma (Amazon), Tarun Sharma (Amazon) and Joaquin Delgado (Amazon)
Live Session
Positive-Sum Impact of Multistakeholder Recommender Systems for Urban Tourism Promotion and User Utility
Pavel Merinov (Free University of Bozen-Bolzano) and Francesco Ricci (Free University of Bozen-Bolzano)
Live Session
Powerful A/B-Testing Metrics and Where to Find Them
Olivier Jeunen (ShareChat), Shubham Baweja (ShareChat), Neeti Pokharna (ShareChat) and Aleksei Ustimenko (ShareChat)
Live Session
Privacy Preserving Conversion Modeling in Data Clean Room
Kungang Li (Pinterest), Xiangyi Chen (Pinterest), Ling Leng (Pinterest), Jiajing Xu (Pinterest), Jiankai Sun (Pinterest) and Behnam Rezaei (Pinterest)
Live Session
Promoting Two-sided Fairness with Adaptive Weights for Providers and Customers in Recommendation
Lanling Xu (Gaoling School of Artificial Intelligence, Renmin University of China), Zihan Lin (School of Information, Renmin University of China), Jinpeng Wang (Meituan Group, Beijing), Sheng Chen (Meituan Group, Beijing), Wayne Xin Zhao (Gaoling School of Artificial Intelligence, Renmin University of China) and Ji-Rong Wen (Renmin University of China)
Live Session
Prompt Tuning for Item Cold-start Recommendation
Yuezihan Jiang (Kuaishou Technology), Gaode Chen (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Wenhan Zhang (Peking University), Jingchi Wang (Peking University), Yinjie Jiang (Kuaishou Technology), Qi Zhang (Kuaishou Technology), Jingjian Lin (Kuaishou Technology), Peng Jiang (Kuaishou Technology) and Kaigui Bian (Peking University)
Live Session
Putting Popularity Bias Mitigation to the Test: A User-Centric Evaluation in Music Recommenders
Robin Ungruh (Delft University of Technology), Karlijn Dinnissen (Utrecht University), Anja Volk (Utrecht University), Maria Soledad Pera (Delft University of Technology) and Hanna Hauptmann (Utrecht University)
Live Session
RPAF: A Reinforcement Prediction-Allocation Framework for Cache Allocation in Large-Scale Recommender Systems
Shuo Su (Kuaishou Technology), Xiaoshuang Chen (Kuaishou Technology), Yao Wang (Kuaishou Technology), Yulin Wu (Kuaishou Technology), Ziqiang Zhang (Tsinghua University), Kaiqiao Zhan (Kuaishou Technology), Ben Wang (Kuaishou Technology) and Kun Gai (No affiliation)
Live Session
RPAF: A Reinforcement Prediction-Allocation Framework for Cache Allocation in Large-Scale Recommender Systems
Shuo Su (Kuaishou Technology), Xiaoshuang Chen (Kuaishou Technology), Yao Wang (Kuaishou Technology), Yulin Wu (Kuaishou Technology), Ziqiang Zhang (Tsinghua University), Kaiqiao Zhan (Kuaishou Technology), Ben Wang (Kuaishou Technology) and Kun Gai (No affiliation)
Live Session
Ranking Across Different Content Types: The Robust Beauty of Multinomial Blending
Jan Malte Lichtenberg (Amazon), Giuseppe Di Benedetto (Amazon) and Matteo Ruffini (Amazon)
Live Session
Ranking-Aware Unbiased Post-Click Conversion Rate Estimation via AUC Optimization on Entire Exposure Space
Yu Liu (School of Artificial Intelligence, Nanjing University), Qinglin Jia (Huawei Noah’s Ark Lab), Shuting Shi (Huawei TECHNOLOGIES Co., Ltd), Chuhan Wu (Huawei Noah’s Ark Lab), Zhaocheng Du (Huawei Noah’s Ark Lab), Zheng Xie (Nanjing University), Ruiming Tang (Huawei Noah’s Ark Lab), Muyu Zhang (Huawei TECHNOLOGIES Co., Ltd) and Ming Li (School of Artificial Intelligence, Nanjing University)
Live Session
ReChorus2.0: A Modular and Task-Flexible Recommendation Library
Jiayu Li (DCST, Tsinghua University; Quan Cheng Laboratory), Hanyu Li (DCST, Tsinghua University; Quan Cheng Laboratory), Zhiyu He (DCST, Tsinghua University), Weizhi Ma (AIR, Tsinghua University), Peijie Sun (DCST, Tsinghua University), Min Zhang (DCST, Tsinghua University; Quan Cheng Laboratory) and Shaoping Ma (DCST, Tsinghua University)
Live Session
ReLand: Integrating Large Language Models’ Insights into Industrial Recommenders via a Controllable Reasoning Pool
Changxin Tian (Ant Group), Binbin Hu (Ant Group), Chunjing Gan (Ant Group), Haoyu Chen (Ant Group), Zhuo Zhang (Ant Group), Li Yu (Ant Group), Ziqi Liu (Ant Group), Zhiqiang Zhang (Ant Financial Services Group), Jun Zhou (Ant Financial) and Jiawei Chen (Zhejiang University)
Live Session
RePlay: a Recommendation Framework for Experimentation and Production Use
Alexey Vasilev (Sber AI Lab), Anna Volodkevich (Sber AI Lab), Denis Kulandin (Sber AmazMe), Tatiana Bysheva (Sber AmazMe) and Anton Klenitskiy (Sber AI Lab)
Live Session
RecSys 2024 Closing
Tommaso Di Noia, Pasquale Lops
Live Session
RecSys 2024 Opening Session
Tommaso Di Noia, Pasquale Lops, Thorsten Joachims, Katrien Verbert
Live Session
Recommender Systems Algorithm Selection for Ranking Prediction on Implicit Feedback Datasets
Lukas Wegmeth (University of Siegen), Tobias Vente (University of Siegen) and Joeran Beel (University of Siegen)
Live Session
Recommending Healthy and Sustainable Meals exploiting Food Retrieval and Large Language Models
Alessandro Petruzzelli (Dipartimento di Informatica - University of Bari), Cataldo Musto (Dipartimento di Informatica - University of Bari), Michele Ciro Di Carlo (Dipartimento di Informatica - University of Bari), Giovanni Tempesta (Dipartimento di Informatica - University of Bari) and Giovanni Semeraro (Dipartimento di Informatica - University of Bari)
Live Session
Recommending Personalised Targeted Training Adjustments for Marathon Runners
Ciara Feely (University College Dublin), Brian Caulfield (University College Dublin), Aonghus Lawlor (University College Dublin) and Barry Smyth (University College Dublin)
Live Session
Repeated Padding for Sequential Recommendation
Yizhou Dang (Northeastern University), Yuting Liu (Northeastern University), Enneng Yang (Northeastern University), Guibing Guo (Northeastern University), Linying Jiang (Northeastern University), Xingwei Wang (Northeastern University) and Jianzhe Zhao (Northeastern University)
Live Session
Reproducibility and Analysis of Scientific Dataset Recommendation Methods
Ornella Irrera (Department of Information Engineering, University of Padua), Matteo Lissandrini (Department of Foreign Languages and Literatures at the University of Verona, Italy), Daniele Dell’Aglio (Department of Computer Science, Aalborg University, Denmark) and Gianmaria Silvello (Department of Information Engineering, University of Padua, Italy)
Live Session
Reproducibility of LLM-based Recommender Systems: the case study of P5 paradigm
Pasquale Lops (University of Bari Aldo Moro), Antonio Silletti (University of Bari Aldo Moro), Marco Polignano (University of Bari Aldo Moro), Cataldo Musto (University of Bari Aldo Moro) and Giovanni Semeraro (University of Bari Aldo Moro)
Live Session
Reproducing Popularity Bias in Recommendation: The Effect of Evaluation Strategies
Savvina Daniil, Mirjam Cuper, Cynthia C. S. Liem, Jacco van Ossenbruggen, and Laura Hollink
Live Session
Revisiting BPR: A Replicability Study of a Common Recommender System Baseline
Aleksandr Milogradskii (National Research University Higher School of Economics, Tinkoff), Oleg Lashinin (Moscow Institute of Physics and Technology, Tinkoff), Alexander P (Independent Researcher), Marina Ananyeva (National Research University Higher School of Economics, Tinkoff) and Sergey Kolesnikov (Tinkoff.AI)
Live Session
Revisiting LightGCN: Unexpected Inflexibility, Inconsistency, and A Remedy Towards Improved Recommendation
Geon Lee (Korea Advanced Institute of Science and Technology), Kyungho Kim (Korea Advanced Institute of Science and Technology) and Kijung Shin (Korea Advanced Institute of Science and Technology)
Live Session
Right Tool, Right Job: Recommendation for Repeat and Exploration Consumption in Food Delivery
Jiayu Li (Tsinghua University), Aixin Sun (Nanyang Technological University), Weizhi Ma (Tsinghua University), Peijie Sun (Hefei University of Technology, School of Computer and Information) and Min Zhang (Tsinghua University)
Live Session
Right Tool, Right Job: Recommendation for Repeat and Exploration Consumption in Food Delivery
Jiayu Li (Tsinghua University), Aixin Sun (Nanyang Technological University), Weizhi Ma (Tsinghua University), Peijie Sun (Hefei University of Technology, School of Computer and Information) and Min Zhang (Tsinghua University)
Live Session
Rs4rs: Semantically Find Recent Publications from Top Recommendation System-Related Venues
Tri Kurniawan Wijaya (Huawei Research), Edoardo D'Amico (Huawei Research), Gabor Fodor (Huawei Research) and Manuel Valentim Loureiro (Huawei Research)
Live Session
Scalable Cross-Entropy Loss for Sequential Recommendations with Large Item Catalogs
Gleb Mezentsev (Skoltech), Danil Gusak (Skoltech, HSE), Ivan Oseledets (AIRI, Skoltech) and Evgeny Frolov (AIRI, HSE, Skoltech)
Live Session
Scale-Invariant Learning-to-Rank
Christian Sommeregger (Expedia Group), Alessio Petrozziello (Expedia Group), Xiaoke Liu (Expedia Group) and Ye-Sheen Lim (Expedia Group).
Live Session
Scaling Law of Large Sequential Recommendation Models
Gaowei Zhang (Renmin University of China), Yupeng Hou (University of California San Diego), Hongyu Lu (WeChat, Tencent), Yu Chen (WeChat, Tencent), Wayne Xin Zhao (Renmin University of China) and Ji-Rong Wen (Renmin University of China)
Live Session
Scaling Law of Large Sequential Recommendation Models
Gaowei Zhang (Renmin University of China), Yupeng Hou (University of California San Diego), Hongyu Lu (WeChat, Tencent), Yu Chen (WeChat, Tencent), Wayne Xin Zhao (Renmin University of China) and Ji-Rong Wen (Renmin University of China)
Live Session
Scene-wise Adaptive Network for Dynamic Cold-start Scenes Optimization in CTR Prediction
Wenhao Li (Huazhong University of Science and Technology), Jie Zhou (Beihang University), Chuan Luo (Beihang University), Chao Tang (Meituan), Kun Zhang (Meituan) and Shixiong Zhao (The University of Hong Kong)
Live Session
Scene-wise Adaptive Network for Dynamic Cold-start Scenes Optimization in CTR Prediction
Wenhao Li (Huazhong University of Science and Technology), Jie Zhou (Beihang University), Chuan Luo (Beihang University), Chao Tang (Meituan), Kun Zhang (Meituan) and Shixiong Zhao (The University of Hong Kong)
Live Session
SeCor: Aligning Semantic and Collaborative representations by Large Language Models for Next-Point-of-Interest Recommendations
Shirui Wang (Tongji University), Bohan Xie (Tongji university), Ling Ding (Tongji University), Xiaoying Gao (Tongji University), Jianting Chen (Tongji University) and Yang Xiang (Tongji University)
Live Session
SeCor: Aligning Semantic and Collaborative representations by Large Language Models for Next-Point-of-Interest Recommendations
Shirui Wang (Tongji University), Bohan Xie (Tongji university), Ling Ding (Tongji University), Xiaoying Gao (Tongji University), Jianting Chen (Tongji University) and Yang Xiang (Tongji University)
Live Session
Self-Attentive Sequential Recommendations with Hyperbolic Representations
Evgeny Frolov (AIRI, Skolkovo Institute of Science and Technology), Tatyana Matveeva (Higher School of Economics, Saint Petersburg State University), Leyla Mirvakhabova (Skolkovo Institute of Science and Technology) and Ivan Oseledets (AIRI, Skolkovo Institute of Science and Technology)
Live Session
Self-Auxiliary Distillation for Sample Efficient Learning in Google-Scale Recommenders
Yin Zhang (Google DeepMind), Ruoxi Wang (Google DeepMind), Xiang Li (Google, Inc), Tiansheng Yao (Google, Inc), Andrew Evdokimov (Google, Inc), Jonathan Valverde (Google DeepMind), Yuan Gao (Google, Inc), Jerry Zhang (Google, Inc), Evan Ettinger (Google, Inc), Ed H. Chi (Google DeepMind) and Derek Zhiyuan Cheng (Google DeepMind)
Live Session
SelfCF: A Simple Framework for Self-supervised Collaborative Filtering
Xin Zhou, Aixin Sun, Yong Liu, Jie Zhang, Chunyan Miao
Live Session
Short-form Video Needs Long-term Interests: An Industrial Solution for Serving Large User Sequence Models
Yuening Li (Google), Diego Uribe (Google), Chuan He (Google), Jiaxi Tang (Google DeepMind), Qingyun Liu (Google DeepMind), Junjie Shan (Google), Ben Most (Google), Kaushik Kalyan (Google), Shuchao Bi (Google), Xinyang Yi (Google DeepMind), Lichan Hong (Google DeepMind), Ed Chi (Google DeepMind) and Liang Liu (Google).
Live Session
Sliding Window Training - Utilizing Historical Recommender Systems Data for Foundation Models
Swanand Joshi (Netflix), Yesu Feng (Netflix), Ko-Jen Hsiao (Netflix), Zhe Zhang (Netflix) and Sudarshan Lamkhede (Netflix)
Live Session
Social Choice for Heterogeneous Fairness in Recommendation
Amanda Aird (University of Colorado Boulder), Elena Štefancová (Comenius University Bratislava), Cassidy All (University of Colorado Boulder), Amy Voida (University of Colorado Boulder), Martin Homola (Comenius University Bratislava), Nicholas Mattei (Tulane University) and Robin Burke (University of Colorado Boulder)
Live Session
Societal Sorting as a Systemic Risk of Recommenders
Luke Thorburn (King's College London), Maria Polukarov (King's College London) and Carmine Ventre (King's College London)
Live Session
Stalactite: toolbox for fast prototyping of vertical federated learning systems
Anastasiia Zakharova (ITMO University), Dmitriy Alexandrov (ITMO University), Mariia Khodorchenko (ITMO University), Nikolay Butakov (ITMO University), Alexey Vasilev (Sber AI Lab), Maxim Savchenko (Sber AI Lab) and Alexander Grigorievskiy (Sber AI Lab)
Live Session
Supporting Knowledge Workers through Personal Information Assistance with Context-aware Recommender Systems
Mahta Bakhshizadeh (German Research Center for Artificial Intelligence – DFKI)
Live Session
TLRec: A Transfer Learning Framework to Enhance Large Language Models for Sequential Recommendation Tasks
Jiaye Lin (Tsinghua University), Shuang Peng (Zhejiang Lab), Zhong Zhang (Tencent AI Lab) and Peilin Zhao (Tencent AI Lab)
Live Session
Taming the One-Epoch Phenomenon in Online Recommendation System by Two-stage Contrastive ID Pre-training
Yi-Ping Hsu (Pinterest), Po-Wei Wang (Pinterest), Chantat Eksombatchai (Pinterest) and Jiajing Xu (Pinterest)
Live Session
The Elephant in the Room: Rethinking the Usage of Pre-trained Language Model in Sequential Recommendation
Zekai Qu (China University of Geosciences Beijing), Ruobing Xie (Tencent Inc.), Chaojun Xiao (Tsinghua University), Zhanhui Kang (Tencent Inc.) and Xingwu Sun (Tencent Inc.)
Live Session
The Fault in Our Recommendations: On the Perils of Optimizing the Measurable
Omar Besbes (Columbia University), Yash Kanoria (Columbia University) and Akshit Kumar (Columbia University)
Live Session
The MovieLens Beliefs Dataset: Collecting Pre-Choice Data for Online Recommender Systems
Guy Aridor (Northwestern Kellogg), Duarte Goncalves (University College London), Ruoyan Kong (TikTok), Daniel Kluver (University of Minnesota – Twin Cities) and Joseph Konstan (University of Minnesota – Twin Cities)
Live Session
The Role of Unknown Interactions in Implicit Matrix Factorization — A Probabilistic View
Joey De Pauw (University of Antwerp) and Bart Goethals (University of Antwerp)
Live Session
The Role of Unknown Interactions in Implicit Matrix Factorization — A Probabilistic View
Joey De Pauw (University of Antwerp) and Bart Goethals (University of Antwerp)
Live Session
Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation
Xing Tang (Tencent), Yang Qiao (FIT, Tencent), Fuyuan Lyu (McGill University), Dugang Liu (Shenzhen University) and Xiuqiang He (FiT,Tencent)
Live Session
Toward 100TB Recommendation Models with Embedding Offloading
Intaik Park (Meta), Paul Zhang (Meta), Ehsan Ardestani (Meta), Damian Reeves (Meta), Sarunya Pumma (Meta), Henry Tsang (Meta), Levy Zhao (Meta), Jian He (Meta), Joshua Deng (Meta), Dennis Van der Staay (Meta) and Yu Guo (Meta)
Live Session
Towards Empathetic Conversational Recommender Systems
Xiaoyu Zhang (Shandong University), Ruobing Xie (Tencent), Yougang Lyu (Shandong University), Xin Xin (Shandong University), Pengjie Ren (Shandong University), Mingfei Liang (Tencent), Bo Zhang (Tencent), Zhanhui Kang (Tencent), Maarten de Rijke (University of Amsterdam) and Zhaochun Ren (Leiden University)
Live Session
Towards Green Recommender Systems: Investigating the Impact of Data Reduction on Carbon Footprint and Algorithm Performances
Giuseppe Spillo (University of Bari), Allegra De Filippo (DISI Università di Bologna), Cataldo Musto (Dipartimento di Informatica - University of Bari), Michela Milano (DISI Universita' di Bologna) and Giovanni Semeraro (University of Bari)
Live Session
Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models
Yunjia Xi (Shanghai Jiao Tong University), Weiwen Liu (Huawei Noah’s Ark Lab), Jianghao Lin (Shanghai Jiao Tong University), Xiaoling Cai (Consumer Business Group, Huawei), Hong Zhu (Consumer Business Group, Huawei), Jieming Zhu (Huawei Noah’s Ark Lab), Bo Chen (Huawei Noah’s Ark Lab), Ruiming Tang (Huawei Noah’s Ark Lab), Weinan Zhang (Shanghai Jiao Tong University) and Yong Yu (Shanghai Jiao Tong University)
Live Session
Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models
Yunjia Xi (Shanghai Jiao Tong University), Weiwen Liu (Huawei Noah's Ark Lab), Jianghao Lin (Shanghai Jiao Tong University), Xiaoling Cai (Consumer Business Group, Huawei), Hong Zhu (Consumer Business Group, Huawei), Jieming Zhu (Huawei Noah's Ark Lab), Bo Chen (Huawei Noah's Ark Lab), Ruiming Tang (Huawei Noah's Ark Lab), Weinan Zhang (Shanghai Jiao Tong University) and Yong Yu (Shanghai Jiao Tong University)
Live Session
Towards Sustainable Recommendations in Urban Tourism
Pavel Merinov (Free University of Bozen-Bolzano)
Live Session
Towards Symbiotic Recommendations: Leveraging LLMs for Conversational Recommendation Systems
Alessandro Petruzzelli (University of Bari Aldo Moro)
Live Session
Towards Understanding The Gaps of Offline And Online Evaluation Metrics: Impact of Series vs. Movie Recommendations
Bora Edizel (Warner Bros. Discovery), Tim Sweetser (StubHub), Ashok Chandrashekar (Warner Bros. Discovery), Kamilia Ahmadi (Warner Bros. Discovery) and Puja Das (Warner Bros. Discovery)
Live Session
Transformers Meet ACT-R: Repeat-Aware and Sequential Listening Session Recommendation
Viet-Anh Tran (Deezer Research), Guillaume Salha-Galvan (Deezer Research), Bruno Sguerra (Deezer Research) and Romain Hennequin (Deezer Research)
Live Session
Understanding Fairness in Recommender Systems: A Healthcare Perspective
Veronica Kecki (University of Gothenburg) and Alan Said (University of Gothenburg)
Live Session
Understanding the Contribution of Recommendation Algorithms on Misinformation Recommendation and Misinformation Dissemination on Social Networks
Royal Pathak, Francesca Spezzano, Maria Soledad Pera
Live Session
Unified Denoising Training for Recommendation
Haoyan Chua (Nanyang Technological University), Yingpeng Du (Peking University), Zhu Sun (Agency for Science, Technology and Research (A*STAR)), Ziyan Wang (Nanyang Technological University), Jie Zhang (Nanyang Technological University) and Yew-Soon Ong (Nanyang Technological University)
Live Session
Unified Denoising Training for Recommendation
Haoyan Chua (Nanyang Technological University), Yingpeng Du (Peking University), Zhu Sun (Agency for Science, Technology and Research (A*STAR)), Ziyan Wang (Nanyang Technological University), Jie Zhang (Nanyang Technological University) and Yew-Soon Ong (Nanyang Technological University)
Live Session
Unleashing the Retrieval Potential of Large Language Models in Conversational Recommender Systems
Ting Yang (Hong Kong Baptist University) and Li Chen (Hong Kong Baptist University)
Live Session
Unlocking the Hidden Treasures: Enhancing Recommendations with Unlabeled Data
Yuhan Zhao (Harbin Engineering University), Rui Chen (Harbin Engineering University), Qilong Han (Harbin Engineering University), Hongtao Song (Harbin Engineering University) and Li Chen (Hong Kong Baptist University)
Live Session
User knowledge prompt for sequential recommendation
Yuuki Tachioka (Denso IT Laboratory)
Live Session
Utilizing Non-click Samples via Semi-supervised Learning for Conversion Rate Prediction
Jiahui Huang (University of Science and Technology of China), Lan Zhang (University of Science and Technology of China), Junhao Wang (University of Science and Technology of China), Shanyang Jiang (University of Science and Technology of China), Dongbo Huang (Tencent), Cheng Ding (Tencent) and Lan Xu (Tencent)
Live Session
What to compare? Towards understanding user sessions on price comparison platforms
Ahmadou Wagne (TU Wien) and Julia Neidhardt (TU Wien)
Live Session
Where are the values? A systematic literature review on news recommender systems
Christine Bauer, Chandni Bagchi, Olusanmi Hundogan, and Karin van Es
Live Session
Why the Shooting in the Dark Method Dominates Recommender Systems Practice
David Rohde (Criteo)
Live Session
beeFormer: Bridging the Gap Between Semantic and Interaction Similarity in Recommender Systems
Vojtech Vancura (Czech Technical University), Pavel Kordik (Czech Technical University) and Milan Straka (UFAL, Charles University in Prague)
Live Session
Δ-OPE: Off-Policy Estimation with Pairs of Policies
Olivier Jeunen (ShareChat) and Aleksei Ustimenko (ShareChat)
Live Session
How to Access Recordings
Tutorial recordings, if available, will be here on the library until January 31, 2025.
A Tutorial on Feature Interpretation in Recommender Systems
View on ACM LibraryZhaocheng Du, Chuhan Wu, Qinglin Jia, Jieming Zhu and Xu Chen
Live Session
Computational Methods for Designing Human-Centered Recommender Systems: A Case Study Approach Intersecting Visual Arts and Healthcare
View on ACM LibraryBereket Yilma
Live Session
Conducting Recommender Systems User Studies Using POPROX
View on ACM LibraryRobin Burke, Joseph Konstan and Michael Ekstrand
Live Session
Conducting User Experiments in Recommender Systems
View on ACM LibraryBart Knijnenburg and Edward Malthouse
Live Session
Deep Recommendation using Graphs
View on ACM LibraryPanagiotis Symeonidis
Live Session
Economics of Recommender Systems
View on ACM LibraryEmilio Calvano, Giacomo Calzolari, Vincenzo Denicolo and Sergio Pastorello
Live Session
How to Access Recordings
Recordings will be available here in the library until January 31, 2025.
AltRecSys: A Workshop on Alternative, Unexpected, and Critical Work on Recommendation
Organizers: Michael Ekstrand (Drexel University), Maria Soledad Pera (Delft University of Technology) and Alan Said (University of Gothenburg)
Live Session
CARS: Workshop on Context-Aware Recommender Systems
Organizers: Gediminas Adomavicius (University of Minnesota), Konstantin Bauman (Temple University), Bamshad Mobasher (De-Paul University Chicago), Alexander Tuzhilin (New York University) and Moshe Unger (Tel Aviv University)
Live Session
CONSEQUENCES: The 3rd Workshop on Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems
Organizers: Olivier Jeunen (ShareChat), Harrie Oosterhuis (Radboud University), Yuta Saito (Cornell University), Flavian Vasile (Criteo) and Yixin Wang (University of Michigan)
Live Session
EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models
Organizers: Irene Li (University of Tokyo), Ruihai Dong (University College Dublin), Lei Li (Hong Kong Baptist University) and Li Chen (Hong Kong Baptist University)
Live Session
FAccTRec 2024: The 7th Workshop on Responsible Recommendation
Organizers: Michael D. Ekstrand (Drexel University), Toshihiro Kamishima (National Institute of Advanced Industrial Science and Technology), Amifa Raj (Microsoft) and Karlijn Dinnissen (University of Utrecht)
Live Session
HealthRecSys: 6th ACM RecSys Workshop on Health Recommender Systems
Organizers: Hanna Hauptmann (University of Utrecht), Christoph Trattner (University of Bergen) and Helma Torkamaan (Delft University of Technology)
Live Session
INRA: 12th International Workshop on News Recommendation and Analytics
Organizers: Benjamin Kille (NTNU), Andreas Lommatzsch (TU Berlin), Célina Treuillier (Université de Lorraine, CNRS, LORIA), Vandana Yadav (NTNU) and Özlem Özgöbek (NTNU)
Live Session
INTROSPECTIVES: Reflections on Recommender Systems Past, Present, and Future
Organizers: Alan Said (University of Gothenburg), Christine Bauer (Paris Lodron University Salzburg) and Eva Zangerle (University of Innsbruck)
Live Session
IntRS 2024: 11th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems
Organizers: Peter Brusilovsky (University of Pittsburgh), Marco de Gemmis (University of Bari), Alexander Felfernig (TU Graz), Marco Polignano (University of Bari), Giovanni Semeraro (University of Bari) and Martijn Willemsen (Eindhoven University of Technology)
Live Session
KaRS: Sixth Knowledge-aware and Conversational Recommender Systems Workshop
Organizers: Vito Walter Anelli (Polytechnic University of Bari), Antonio Ferrara (Polytechnic University of Bari), Cataldo Musto (University of Bari), Fedelucio Narducci (Polytechnic University of Bari), Azzurra Ragone (University of Bari) and Markus Zanker (Free University of Bozen-Bolzano)
Live Session
MuRS2024: 2nd Music Recommender Systems Workshop
Organizers: Andres Ferraro (Pandora-SiriusXM), Lorenzo Porcaro (Joint Research Centre, European Commission), Peter Knees (TU Vienna) and Christine Bauer (Paris Lodron University Salzburg)
Live Session
NORMalize: The Second Workshop on Normative Design and Evaluation of Recommender Systems
Organizers: Alain D. Starke (ASCOR, University of Amsterdam), Sanne Vrijenhoek (University of Amsterdam), Lien Michiels (University of Antwerp), Johannes Kruse (Ekstra Bladet) and Nava Tintarev (Maastricht University)
Live Session
ROEGEN: The 1st International Workshop on Risks, Opportunities, and Evaluation of Generative Models in Recommendation
Organizers: Yashar Deldjoo (Polytechnic University of Bari), Julian McAuley (UC San Diego), Scott Sanner (University of Toronto), Pablo Castells (Universidad Autónoma de Madrid), Shuai Zhang (Amazon Web Services AI), and Enrico Palumbo (Spotify)
Live Session
RecSoGood 2024: First International Workshop on Recommender Systems for Sustainability and Social Good
Organizers: Ludovico Boratto (University of Cagliari), Allegra De Filippo (University of Bologna), Elisabeth Lex (Graz University of Technology) and Francesco Ricci (Free University of Bozen-Bolzano)
Live Session
RecSys Challenge
Live Session
RecSys in HR 2024: Fourth Workshop on Recommender Systems for Human Resources
Organizers: Toine Bogers (IT University of Copenhagen), David Graus (Randstad), Mesut Kaya (Aalborg University), Chris Johnson (Indeed), Jens-Joris Decorte (TechWolf and University College Ghent) and Tijl De Bie (University of Ghent)
Live Session
RecTemp: Temporal Reasoning in Recommendation Systems
Organizers: Adir Solomon (University of Haifa), Tsvi Kuflik (University of Haifa), Bracha Shapira (Ben Gurion University of the Negev, eBay R&D center) and Ido Guy (Meta and Ben Gurion University of the Negev)
Live Session
RecTour: Workshop on Recommenders in Tourism
Organizers: Julia Neidhardt (TU Vienna), Tsvi Kuflik (University of Haifa), Amit Livne (Booking.com and Ben Gurion University of the Negev) and Markus Zanker (Free University of Bozen-Bolzano)
Live Session
RobustRecSys @ RecSys2024: Design, Evaluation and Deployment of Robust Recommender Systems
Organizers: Valerio Guarrasi (University Campus Bio-Medico of Rome), Federico Siciliano (Sapienza University of Rome) and Fabrizio Silvestri (Sapienza University of Rome)
Live Session
SURE 2024: Workshop on Strategic and Utility-aware REcommendation
Organizers: Himan Abdollahpouri (Spotify), Tonia Danylenko (Spotify), Masoud Mansoury (TU Delft), Babak Loni (Meta), Daniel Russo (Columbia University) and Mihajlo Grbovic (Airbnb)
Live Session
VideoRecSys + LargeRecSys 2024
Organizers: Khushhall Chandra Mahajan (Meta), Amey Porobo Dharwadker (Meta), Saurabh Gupta (Meta), Brad Schumitsch (Meta), Arnab Bhadury (Google), Ding Tong (Netflix), Liang Liu (Google) and Ko-Jen Hsiao (Netflix)