| 2023 | 10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS'23). Peter Brusilovsky, Marco de Gemmis, Alexander Felfernig, Pasquale Lops, Marco Polignano, Giovanni Semeraro, Martijn C. Willemsen |
| 2023 | A Lightweight Method for Modeling Confidence in Recommendations with Learned Beta Distributions. Norman Knyazev, Harrie Oosterhuis |
| 2023 | A Model-Agnostic Framework for Recommendation via Interest-aware Item Embeddings. Amit Kumar Jaiswal, Yu Xiong |
| 2023 | A Multi-view Graph Contrastive Learning Framework for Cross-Domain Sequential Recommendation. Zitao Xu, Weike Pan, Zhong Ming |
| 2023 | A Probabilistic Position Bias Model for Short-Video Recommendation Feeds. Olivier Jeunen |
| 2023 | ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction. Haoxuan Li, Taojun Hu, Zetong Xiong, Chunyuan Zheng, Fuli Feng, Xiangnan He, Xiao-Hua Zhou |
| 2023 | Accelerating Creator Audience Building through Centralized Exploration. Buket Baran, Guilherme Dinis Junior, Antonina Danylenko, Olayinka S. Folorunso, Gösta Forsum, Maksym Lefarov, Lucas Maystre, Yu Zhao |
| 2023 | Acknowledging Dynamic Aspects of Trust in Recommender Systems. Imane Akdim |
| 2023 | AdaptEx: A Self-Service Contextual Bandit Platform. William Black, Ercument Ilhan, Andrea Marchini, Vilda Markeviciute |
| 2023 | Adaptive Collaborative Filtering with Personalized Time Decay Functions for Financial Product Recommendation. Ashraf Ghiye, Baptiste Barreau, Laurent Carlier, Michalis Vazirgiannis |
| 2023 | Advancing Automation of Design Decisions in Recommender System Pipelines. Tobias Vente |
| 2023 | Adversarial Collaborative Filtering for Free. Huiyuan Chen, Xiaoting Li, Vivian Lai, Chin-Chia Michael Yeh, Yujie Fan, Yan Zheng, Mahashweta Das, Hao Yang |
| 2023 | Adversarial Sleeping Bandit Problems with Multiple Plays: Algorithm and Ranking Application. Jianjun Yuan, Wei Lee Woon, Ludovik Coba |
| 2023 | Alleviating the Long-Tail Problem in Conversational Recommender Systems. Zhipeng Zhao, Kun Zhou, Xiaolei Wang, Wayne Xin Zhao, Fan Pan, Zhao Cao, Ji-Rong Wen |
| 2023 | An Exploration of Sentence-Pair Classification for Algorithmic Recruiting. Mesut Kaya, Toine Bogers |
| 2023 | An Industrial Framework for Personalized Serendipitous Recommendation in E-commerce. Zongyi Wang, Yanyan Zou, Anyu Dai, Linfang Hou, Nan Qiao, Luobao Zou, Mian Ma, Zhuoye Ding, Sulong Xu |
| 2023 | Analysis Operations for Constraint-based Recommender Systems. Sebastian Lubos, Viet-Man Le, Alexander Felfernig, Thi Ngoc Trang Tran |
| 2023 | Analyzing Accuracy versus Diversity in a Health Recommender System for Physical Activities: a Longitudinal User Study. Ine Coppens, Luc Martens, Toon De Pessemier |
| 2023 | Augmented Negative Sampling for Collaborative Filtering. Yuhan Zhao, Rui Chen, Riwei Lai, Qilong Han, Hongtao Song, Li Chen |
| 2023 | AutoOpt: Automatic Hyperparameter Scheduling and Optimization for Deep Click-through Rate Prediction. Yujun Li, Xing Tang, Bo Chen, Yimin Huang, Ruiming Tang, Zhenguo Li |
| 2023 | BVAE: Behavior-aware Variational Autoencoder for Multi-Behavior Multi-Task Recommendation. Qianzhen Rao, Yang Liu, Weike Pan, Zhong Ming |
| 2023 | BehavRec: Workshop on Recommendations for Behavior Change. Amon Rapp, Federica Cena, Christoph Trattner, Rita Orji, Julita Vassileva, Alain Starke |
| 2023 | Beyond Labels: Leveraging Deep Learning and LLMs for Content Metadata. Saurabh Agrawal, John Trenkle, Jaya Kawale |
| 2023 | Beyond the Sequence: Statistics-Driven Pre-training for Stabilizing Sequential Recommendation Model. Sirui Wang, Peiguang Li, Yunsen Xian, Hongzhi Zhang |
| 2023 | Bootstrapped Personalized Popularity for Cold Start Recommender Systems. Iason Chaimalas, Duncan Martin Walker, Edoardo Gruppi, Benjamin Richard Clark, Laura Toni |
| 2023 | Broadening the Scope: Evaluating the Potential of Recommender Systems beyond prioritizing Accuracy. Vincenzo Paparella, Dario Di Palma, Vito Walter Anelli, Tommaso Di Noia |
| 2023 | CONSEQUENCES - The 2nd Workshop on Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems. Olivier Jeunen, Thorsten Joachims, Harrie Oosterhuis, Yuta Saito, Flavian Vasile, Yixin Wang |
| 2023 | CR-SoRec: BERT driven Consistency Regularization for Social Recommendation. Tushar Prakash, Raksha Jalan, Brijraj Singh, Naoyuki Onoe |
| 2023 | Challenges for Anonymous Session-Based Recommender Systems in Indoor Environments. Alessio Ferrato |
| 2023 | Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis. Vito Walter Anelli, Daniele Malitesta, Claudio Pomo, Alejandro Bellogín, Eugenio Di Sciascio, Tommaso Di Noia |
| 2023 | Climbing crags repetitive choices and recommendations. Iustina Ivanova |
| 2023 | Co-occurrence Embedding Enhancement for Long-tail Problem in Multi-Interest Recommendation. Yaokun Liu, Xiaowang Zhang, Minghui Zou, Zhiyong Feng |
| 2023 | Collaborative filtering algorithms are prone to mainstream-taste bias. Pantelis Pipergias Analytis, Philipp Hager |
| 2023 | Complementary Product Recommendation for Long-tail Products. Rastislav Papso |
| 2023 | Contextual Multi-Armed Bandit for Email Layout Recommendation. Yan Chen, Emilian Vankov, Linas Baltrunas, Preston Donovan, Akash Mehta, Benjamin Schroeder, Matthew Herman |
| 2023 | Continual Collaborative Filtering Through Gradient Alignment. Jaime Hieu Do, Hady W. Lauw |
| 2023 | Contrastive Learning with Frequency-Domain Interest Trends for Sequential Recommendation. Yichi Zhang, Guisheng Yin, Yuxin Dong |
| 2023 | Correcting for Interference in Experiments: A Case Study at Douyin. Vivek F. Farias, Hao Li, Tianyi Peng, Xinyuyang Ren, Huawei Zhang, Andrew Zheng |
| 2023 | Creating the next generation of news experience on ekstrabladet.dk with recommender systems. Johannes Kruse, Kasper Lindskow, Michael Riis Andersen, Jes Frellsen |
| 2023 | Customer Lifetime Value Prediction: Towards the Paradigm Shift of Recommender System Objectives. Chuhan Wu, Qinglin Jia, Zhenhua Dong, Ruiming Tang |
| 2023 | DREAM: Decoupled Representation via Extraction Attention Module and Supervised Contrastive Learning for Cross-Domain Sequential Recommender. Xiaoxin Ye, Yun Li, Lina Yao |
| 2023 | Data-free Knowledge Distillation for Reusing Recommendation Models. Cheng Wang, Jiacheng Sun, Zhenhua Dong, Jieming Zhu, Zhenguo Li, Ruixuan Li, Rui Zhang |
| 2023 | Deep Exploration for Recommendation Systems. Zheqing Zhu, Benjamin Van Roy |
| 2023 | Deep Situation-Aware Interaction Network for Click-Through Rate Prediction. Yimin Lv, Shuli Wang, Beihong Jin, Yisong Yu, Yapeng Zhang, Jian Dong, Yongkang Wang, Xingxing Wang, Dong Wang |
| 2023 | Deliberative Diversity for News Recommendations: Operationalization and Experimental User Study. Lucien Heitz, Juliane A. Lischka, Rana Abdullah, Laura Laugwitz, Hendrik Meyer, Abraham Bernstein |
| 2023 | Delivery Hero Recommendation Dataset: A Novel Dataset for Benchmarking Recommendation Algorithms. Yernat Assylbekov, Raghav Bali, Luke Bovard, Christian Klaue |
| 2023 | Demystifying Recommender Systems: A Multi-faceted Examination of Explanation Generation, Impact, and Perception. Giacomo Balloccu |
| 2023 | Denoising Explicit Social Signals for Robust Recommendation. Youchen Sun |
| 2023 | Disentangling Motives behind Item Consumption and Social Connection for Mutually-enhanced Joint Prediction. Youchen Sun, Zhu Sun, Xiao Sha, Jie Zhang, Yew Soon Ong |
| 2023 | Distribution-based Learnable Filters with Side Information for Sequential Recommendation. Haibo Liu, Zhixiang Deng, Liang Wang, Jinjia Peng, Shi Feng |
| 2023 | Domain Disentanglement with Interpolative Data Augmentation for Dual-Target Cross-Domain Recommendation. Jiajie Zhu, Yan Wang, Feng Zhu, Zhu Sun |
| 2023 | EasyStudy: Framework for Easy Deployment of User Studies on Recommender Systems. Patrik Dokoupil, Ladislav Peska |
| 2023 | Efficient Data Representation Learning in Google-scale Systems. Derek Zhiyuan Cheng, Ruoxi Wang, Wang-Cheng Kang, Benjamin Coleman, Yin Zhang, Jianmo Ni, Jonathan Valverde, Lichan Hong, Ed H. Chi |
| 2023 | Enhanced Privacy Preservation for Recommender Systems. Ziqing Wu |
| 2023 | Enhancing Transformers without Self-supervised Learning: A Loss Landscape Perspective in Sequential Recommendation. Vivian Lai, Huiyuan Chen, Chin-Chia Michael Yeh, Minghua Xu, Yiwei Cai, Hao Yang |
| 2023 | Equivariant Contrastive Learning for Sequential Recommendation. Peilin Zhou, Jingqi Gao, Yueqi Xie, Qichen Ye, Yining Hua, Jaeboum Kim, Shoujin Wang, Sunghun Kim |
| 2023 | Evaluating The Effects of Calibrated Popularity Bias Mitigation: A Field Study. Anastasiia Klimashevskaia, Mehdi Elahi, Dietmar Jannach, Lars Skjærven, Astrid Tessem, Christoph Trattner |
| 2023 | Everyone's a Winner! On Hyperparameter Tuning of Recommendation Models. Faisal Shehzad, Dietmar Jannach |
| 2023 | Ex2Vec: Characterizing Users and Items from the Mere Exposure Effect. Bruno Sguerra, Viet-Anh Tran, Romain Hennequin |
| 2023 | Explainable Graph Neural Network Recommenders; Challenges and Opportunities. Amir Reza Mohammadi |
| 2023 | Exploring False Hard Negative Sample in Cross-Domain Recommendation. Haokai Ma, Ruobing Xie, Lei Meng, Xin Chen, Xu Zhang, Leyu Lin, Jie Zhou |
| 2023 | Exploring Unlearning Methods to Ensure the Privacy, Security, and Usability of Recommender Systems. Jens Leysen |
| 2023 | Extended Conversion: Capturing Successful Interactions in Voice Shopping. Elad Haramaty, Zohar S. Karnin, Arnon Lazerson, Liane Lewin-Eytan, Yoelle Maarek |
| 2023 | FAccTRec 2023: The 6th Workshop on Responsible Recommendation. Michael D. Ekstrand, Jean Garcia-Gathright, Nasim Sonboli, Amifa Raj, Karlijn Dinnissen |
| 2023 | Fast and Examination-agnostic Reciprocal Recommendation in Matching Markets. Yoji Tomita, Riku Togashi, Yuriko Hashizume, Naoto Ohsaka |
| 2023 | Fifth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS). Vito Walter Anelli, Pierpaolo Basile, Gerard de Melo, Francesco M. Donini, Antonio Ferrara, Cataldo Musto, Fedelucio Narducci, Azzurra Ragone, Markus Zanker |
| 2023 | Fifth Workshop on Recommender Systems in Fashion and Retail - fashionXrecsys2023. Julia Lasserre, Nima Dokoohaki, Reza Shirvany |
| 2023 | From Research to Production: Towards Scalable and Sustainable Neural Recommendation Models on Commodity CPU Hardware. Anshumali Shrivastava, Vihan Lakshman, Tharun Medini, Nicholas Meisburger, Joshua Engels, David Torres Ramos, Benito Geordie, Pratik Pranav, Shubh Gupta, Yashwanth Adunukota, Siddharth Jain |
| 2023 | Full Index Deep Retrieval: End-to-End User and Item Structures for Cold-start and Long-tail Item Recommendation. Zhen Gong, Xin Wu, Lei Chen, Zhenzhe Zheng, Shengjie Wang, Anran Xu, Chong Wang, Fan Wu |
| 2023 | Generative Learning Plan Recommendation for Employees: A Performance-aware Reinforcement Learning Approach. Zhi Zheng, Ying Sun, Xin Song, Hengshu Zhu, Hui Xiong |
| 2023 | Generative Next-Basket Recommendation. Wenqi Sun, Ruobing Xie, Junjie Zhang, Wayne Xin Zhao, Leyu Lin, Ji-Rong Wen |
| 2023 | Goal-Oriented Multi-Modal Interactive Recommendation with Verbal and Non-Verbal Relevance Feedback. Yaxiong Wu, Craig Macdonald, Iadh Ounis |
| 2023 | Gradient Matching for Categorical Data Distillation in CTR Prediction. Cheng Wang, Jiacheng Sun, Zhenhua Dong, Ruixuan Li, Rui Zhang |
| 2023 | Group Fairness for Content Creators: the Role of Human and Algorithmic Biases under Popularity-based Recommendations. Stefania Ionescu, Aniko Hannak, Nicolò Pagan |
| 2023 | HUMMUS: A Linked, Healthiness-Aware, User-centered and Argument-Enabling Recipe Data Set for Recommendation. Felix Bölz, Diana Nurbakova, Sylvie Calabretto, Armin Gerl, Lionel Brunie, Harald Kosch |
| 2023 | Hessian-aware Quantized Node Embeddings for Recommendation. Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Chin-Chia Michael Yeh, Yan Zheng, Xia Hu, Hao Yang |
| 2023 | Heterogeneous Knowledge Fusion: A Novel Approach for Personalized Recommendation via LLM. Bin Yin, Junjie Xie, Yu Qin, Zixiang Ding, Zhichao Feng, Xiang Li, Wei Lin |
| 2023 | How Should We Measure Filter Bubbles? A Regression Model and Evidence for Online News. Lien Michiels, Jorre T. A. Vannieuwenhuyze, Jens Leysen, Robin Verachtert, Annelien Smets, Bart Goethals |
| 2023 | How Users Ride the Carousel: Exploring the Design of Multi-List Recommender Interfaces From a User Perspective. Benedikt Loepp, Jürgen Ziegler |
| 2023 | Identifying Controversial Pairs in Item-to-Item Recommendations. Junyi Shen, Dayvid V. R. Oliveira, Jin Cao, Brian Knott, Goodman Gu, Sindhu Vijaya Raghavan, Yunye Jin, Nikita Sudan, Rob Monarch |
| 2023 | Improving Group Recommendations using Personality, Dynamic Clustering and Multi-Agent MicroServices. Patrícia Alves, André Martins, Paulo Novais, Goreti Marreiros |
| 2023 | Improving Recommender Systems Through the Automation of Design Decisions. Lukas Wegmeth |
| 2023 | InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models. Kabir Nagrecha, Lingyi Liu, Pablo Delgado, Prasanna Padmanabhan |
| 2023 | Incentivizing Exploration in Linear Contextual Bandits under Information Gap. Huazheng Wang, Haifeng Xu, Chuanhao Li, Zhiyuan Liu, Hongning Wang |
| 2023 | Incorporating Time in Sequential Recommendation Models. Mostafa Rahmani, James Caverlee, Fei Wang |
| 2023 | Initiative transfer in conversational recommender systems. Yuan Ma, Jürgen Ziegler |
| 2023 | Integrating Item Relevance in Training Loss for Sequential Recommender Systems. Andrea Bacciu, Federico Siciliano, Nicola Tonellotto, Fabrizio Silvestri |
| 2023 | Integrating Offline Reinforcement Learning with Transformers for Sequential Recommendation. Xumei Xi, Yuke Zhao, Quan Liu, Liwen Ouyang, Yang Wu |
| 2023 | Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation. Marta Moscati, Christian Wallmann, Markus Reiter-Haas, Dominik Kowald, Elisabeth Lex, Markus Schedl |
| 2023 | Interface Design to Mitigate Inflation in Recommender Systems. Rana Shahout, Yehonatan Peisakhovsky, Sasha Stoikov, Nikhil Garg |
| 2023 | International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with RecSys 2023. Ruiming Tang, Xiaoqiang Zhu, Junfeng Ge, Kuang-Chih Lee, Biye Jiang, Xingxing Wang, Han Zhu, Tao Zhuang, Weiwen Liu, Kan Ren, Weinan Zhang, Xiangyu Zhao |
| 2023 | Interpretable User Retention Modeling in Recommendation. Rui Ding, Ruobing Xie, Xiaobo Hao, Xiaochun Yang, Kaikai Ge, Xu Zhang, Jie Zhou, Leyu Lin |
| 2023 | Introducing LensKit-Auto, an Experimental Automated Recommender System (AutoRecSys) Toolkit. Tobias Vente, Michael D. Ekstrand, Joeran Beel |
| 2023 | Investigating the effects of incremental training on neural ranking models. Benedikt Schifferer, Wenzhe Shi, Gabriel de Souza Pereira Moreira, Even Oldridge, Chris Deotte, Gilberto Titericz, Kazuki Onodera, Praveen Dhinwa, Vishal Agrawal, Chris Green |
| 2023 | Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation. Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He |
| 2023 | KGTORe: Tailored Recommendations through Knowledge-aware GNN Models. Alberto Carlo Maria Mancino, Antonio Ferrara, Salvatore Bufi, Daniele Malitesta, Tommaso Di Noia, Eugenio Di Sciascio |
| 2023 | Knowledge-Aware Recommender Systems based on Multi-Modal Information Sources. Giuseppe Spillo |
| 2023 | Knowledge-based Multiple Adaptive Spaces Fusion for Recommendation. Meng Yuan, Fuzhen Zhuang, Zhao Zhang, Deqing Wang, Jin Dong |
| 2023 | LLM Based Generation of Item-Description for Recommendation System. Arkadeep Acharya, Brijraj Singh, Naoyuki Onoe |
| 2023 | Large Language Model Augmented Narrative Driven Recommendations. Sheshera Mysore, Andrew McCallum, Hamed Zamani |
| 2023 | Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences. Scott Sanner, Krisztian Balog, Filip Radlinski, Ben Wedin, Lucas Dixon |
| 2023 | Learning from Negative User Feedback and Measuring Responsiveness for Sequential Recommenders. Yueqi Wang, Yoni Halpern, Shuo Chang, Jingchen Feng, Elaine Ya Le, Longfei Li, Xujian Liang, Min-Cheng Huang, Shane Li, Alex Beutel, Yaping Zhang, Shuchao Bi |
| 2023 | Learning the True Objectives of Multiple Tasks in Sequential Behavior Modeling. Jiawei Zhang |
| 2023 | Leveling Up the Peloton Homescreen: A System and Algorithm for Dynamic Row Ranking. Natalia Chen, Oinam Nganba Meetei, Nilothpal Talukder, Alexey Zankevich |
| 2023 | Leveraging Large Language Models for Sequential Recommendation. Jesse Harte, Wouter Zorgdrager, Panos Louridas, Asterios Katsifodimos, Dietmar Jannach, Marios Fragkoulis |
| 2023 | LightSAGE: Graph Neural Networks for Large Scale Item Retrieval in Shopee's Advertisement Recommendation. Dang Minh Nguyen, Chenfei Wang, Yan Shen, Yifan Zeng |
| 2023 | Localify.org: Locally-focus Music Artist and Event Recommendation. Douglas Turnbull, April Trainor, Douglas R. Turnbull, Elizabeth Richards, Kieran Bentley, Victoria Conrad, Paul Gagliano, Cassandra Raineault, Thorsten Joachims |
| 2023 | Looks Can Be Deceiving: Linking User-Item Interactions and User's Propensity Towards Multi-Objective Recommendations. Patrik Dokoupil, Ladislav Peska, Ludovico Boratto |
| 2023 | Loss Harmonizing for Multi-Scenario CTR Prediction. Congcong Liu, Liang Shi, Pei Wang, Fei Teng, Xue Jiang, Changping Peng, Zhangang Lin, Jingping Shao |
| 2023 | M3REC: A Meta-based Multi-scenario Multi-task Recommendation Framework. Zerong Lan, Yingyi Zhang, Xianneng Li |
| 2023 | MCM: A Multi-task Pre-trained Customer Model for Personalization. Rui Luo, Tianxin Wang, Jingyuan Deng, Peng Wan |
| 2023 | Masked and Swapped Sequence Modeling for Next Novel Basket Recommendation in Grocery Shopping. Ming Li, Mozhdeh Ariannezhad, Andrew Yates, Maarten de Rijke |
| 2023 | MuRS: Music Recommender Systems Workshop. Andres Ferraro, Peter Knees, Massimo Quadrana, Tao Ye, Fabien Gouyon |
| 2023 | Multi-Relational Contrastive Learning for Recommendation. Wei Wei, Lianghao Xia, Chao Huang |
| 2023 | Multi-task Item-attribute Graph Pre-training for Strict Cold-start Item Recommendation. Yuwei Cao, Liangwei Yang, Chen Wang, Zhiwei Liu, Hao Peng, Chenyu You, Philip S. Yu |
| 2023 | Multiple Connectivity Views for Session-based Recommendation. Yaming Yang, Jieyu Zhang, Yujing Wang, Zheng Miao, Yunhai Tong |
| 2023 | NORMalize: The First Workshop on Normative Design and Evaluation of Recommender Systems. Sanne Vrijenhoek, Lien Michiels, Johannes Kruse, Alain Starke, Nava Tintarev, Jordi Viader Guerrero |
| 2023 | Navigating the Feedback Loop in Recommender Systems: Insights and Strategies from Industry Practice. Ding Tong, Qifeng Qiao, Ting-Po Lee, James McInerney, Justin Basilico |
| 2023 | Nonlinear Bandits Exploration for Recommendations. Yi Su, Minmin Chen |
| 2023 | ORSUM 2023 - 6th Workshop on Online Recommender Systems and User Modeling. João Vinagre, Marie Al-Ghossein, Ladislav Peska, Alípio Mário Jorge, Albert Bifet |
| 2023 | Of Spiky SVDs and Music Recommendation. Darius Afchar, Romain Hennequin, Vincent Guigue |
| 2023 | On Challenges of Evaluating Recommender Systems in an Offline Setting. Aixin Sun |
| 2023 | On the Consistency of Average Embeddings for Item Recommendation. Walid Bendada, Guillaume Salha-Galvan, Romain Hennequin, Thomas Bouabça, Tristan Cazenave |
| 2023 | On the Consistency, Discriminative Power and Robustness of Sampled Metrics in Offline Top-N Recommender System Evaluation. Yang Liu, Alan Medlar, Dorota Glowacka |
| 2023 | Online Matching: A Real-time Bandit System for Large-scale Recommendations. Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi |
| 2023 | Optimizing Long-term Value for Auction-Based Recommender Systems via On-Policy Reinforcement Learning. Ruiyang Xu, Jalaj Bhandari, Dmytro Korenkevych, Fan Liu, Yuchen He, Alex Nikulkov, Zheqing Zhu |
| 2023 | Optimizing Podcast Discovery: Unveiling Amazon Music's Retrieval and Ranking Framework. Geetha Sai Aluri, Paul Greyson, Joaquin Delgado |
| 2023 | OutRank: Speeding up AutoML-based Model Search for Large Sparse Data sets with Cardinality-aware Feature Ranking. Blaz Skrlj, Blaz Mramor |
| 2023 | Overcoming Recommendation Limitations with Neuro-Symbolic Integration. Tommaso Carraro |
| 2023 | Pairwise Intent Graph Embedding Learning for Context-Aware Recommendation. Dugang Liu, Yuhao Wu, Weixin Li, Xiaolian Zhang, Hao Wang, Qinjuan Yang, Zhong Ming |
| 2023 | Personalised Recommendations for the BBC iPlayer: Initial approach and current challenges. Benjamin Richard Clark, Kristine Grivcova, Polina Proutskova, Duncan Martin Walker |
| 2023 | Personalized Category Frequency prediction for Buy It Again recommendations. Amit Pande, Kunal Ghosh, Rankyung Park |
| 2023 | Power Loss Function in Neural Networks for Predicting Click-Through Rate. Ergun Biçici |
| 2023 | Private Matrix Factorization with Public Item Features. Mihaela Curmei, Walid Krichene, Li Zhang, Mukund Sundararajan |
| 2023 | Proceedings of the 17th ACM Conference on Recommender Systems, RecSys 2023, Singapore, Singapore, September 18-22, 2023 Jie Zhang, Li Chen, Shlomo Berkovsky, Min Zhang, Tommaso Di Noia, Justin Basilico, Luiz Pizzato, Yang Song |
| 2023 | Progressive Horizon Learning: Adaptive Long Term Optimization for Personalized Recommendation. Congrui Yi, David Zumwalt, Zijian Ni, Shreya Chakrabarti |
| 2023 | Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders. Bjørnar Vassøy, Helge Langseth, Benjamin Kille |
| 2023 | QUARE: 2nd Workshop on Measuring the Quality of Explanations in Recommender Systems. Oana Inel, Nicolas Mattis, Milda Norkute, Alessandro Piscopo, Timothée Schmude, Sanne Vrijenhoek, Krisztian Balog |
| 2023 | Re2Dan: Retrieval of Medical Documents for e-Health in Danish. Antonela Tommasel, Rafael Pablos-Sarabia, Ira Assent |
| 2023 | ReCon: Reducing Congestion in Job Recommendation using Optimal Transport. Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie |
| 2023 | RecAD: Towards A Unified Library for Recommender Attack and Defense. Changsheng Wang, Jianbai Ye, Wenjie Wang, Chongming Gao, Fuli Feng, Xiangnan He |
| 2023 | RecQR: Using Recommendation Systems for Query Reformulation to correct unseen errors in spoken dialog systems. Manik Bhandari, Mingxian Wang, Oleg Poliannikov, Kanna Shimizu |
| 2023 | RecSys Challenge 2023: Deep Funnel Optimization with a Focus on User Privacy. Rahul Agrawal, Sarang Brahme, Sourav Maitra, Saikishore Kalloori, Abhishek Srivastava, Yong Liu, Athirai A. Irissappane |
| 2023 | Reciprocal Sequential Recommendation. Bowen Zheng, Yupeng Hou, Wayne Xin Zhao, Yang Song, Hengshu Zhu |
| 2023 | Recommenders In the wild - Practical Evaluation Methods. Kim Falk, Morten Arngren |
| 2023 | Reproducibility Analysis of Recommender Systems relying on Visual Features: traps, pitfalls, and countermeasures. Pasquale Lops, Elio Musacchio, Cataldo Musto, Marco Polignano, Antonio Silletti, Giovanni Semeraro |
| 2023 | Reproducibility of Multi-Objective Reinforcement Learning Recommendation: Interplay between Effectiveness and Beyond-Accuracy Perspectives. Vincenzo Paparella, Vito Walter Anelli, Ludovico Boratto, Tommaso Di Noia |
| 2023 | Rethinking Multi-Interest Learning for Candidate Matching in Recommender Systems. Yueqi Xie, Jingqi Gao, Peilin Zhou, Qichen Ye, Yining Hua, Jae Boum Kim, Fangzhao Wu, Sunghun Kim |
| 2023 | Retrieval-augmented Recommender System: Enhancing Recommender Systems with Large Language Models. Dario Di Palma |
| 2023 | Reward innovation for long-term member satisfaction. Gary Tang, Jiangwei Pan, Henry Wang, Justin Basilico |
| 2023 | SPARE: Shortest Path Global Item Relations for Efficient Session-based Recommendation. Andreas Peintner, Amir Reza Mohammadi, Eva Zangerle |
| 2023 | STAN: Stage-Adaptive Network for Multi-Task Recommendation by Learning User Lifecycle-Based Representation. Wanda Li, Wenhao Zheng, Xuanji Xiao, Suhang Wang |
| 2023 | STRec: Sparse Transformer for Sequential Recommendations. Chengxi Li, Yejing Wang, Qidong Liu, Xiangyu Zhao, Wanyu Wang, Yiqi Wang, Lixin Zou, Wenqi Fan, Qing Li |
| 2023 | Scalable Approximate NonSymmetric Autoencoder for Collaborative Filtering. Martin Spisák, Radek Bartyzal, Antonín Hoskovec, Ladislav Peska, Miroslav Tuma |
| 2023 | Scalable Deep Q-Learning for Session-Based Slate Recommendation. Aayush Singha Roy, Edoardo D'Amico, Elias Z. Tragos, Aonghus Lawlor, Neil Hurley |
| 2023 | Scaling Session-Based Transformer Recommendations using Optimized Negative Sampling and Loss Functions. Timo Wilm, Philipp Normann, Sophie Baumeister, Paul-Vincent Kobow |
| 2023 | Sequential Recommendation Models: A Graph-based Perspective. Andreas Peintner |
| 2023 | Stability of Explainable Recommendation. Sairamvinay Vijayaraghavan, Prasant Mohapatra |
| 2023 | Station and Track Attribute-Aware Music Personalization. M. Jeffrey Mei, Oliver Bembom, Andreas F. Ehmann |
| 2023 | TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation. Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He |
| 2023 | Task Aware Feature Extraction Framework for Sequential Dependence Multi-Task Learning. Xuewen Tao, Mingming Ha, Qiongxu Ma, Hongwei Cheng, Wenfang Lin, Xiaobo Guo, Linxun Chen, Bing Han |
| 2023 | The Effect of Third Party Implementations on Reproducibility. Balázs Hidasi, Ádám Tibor Czapp |
| 2023 | The Eleventh International Workshop on News Recommendation and Analytics (INRA'23). Benjamin Kille, Andreas Lommatzsch, Özlem Özgöbek, Peng Liu, Simen Eide, Lemei Zhang |
| 2023 | Third Workshop on Recommender Systems for Human Resources (RecSys in HR 2023). Toine Bogers, David Graus, Mesut Kaya, Chris Johnson, Jens-Joris Decorte |
| 2023 | Third Workshop: Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES 2023). Alan Said, Eva Zangerle, Christine Bauer |
| 2023 | Ti-DC-GNN: Incorporating Time-Interval Dual Graphs for Recommender Systems. Nikita Severin, Andrey V. Savchenko, Dmitrii Kiselev, Maria Ivanova, Ivan Kireev, Ilya Makarov |
| 2023 | Time-Aware Item Weighting for the Next Basket Recommendations. Aleksey Romanov, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov |
| 2023 | Topic-Level Bayesian Surprise and Serendipity for Recommender Systems. Tonmoy Hasan, Razvan C. Bunescu |
| 2023 | Towards Companion Recommenders Assisting Users' Long-Term Journeys. Konstantina Christakopoulou, Minmin Chen |
| 2023 | Towards Health-Aware Fairness in Food Recipe Recommendation. Mehrdad Rostami, Mohammad Aliannejadi, Mourad Oussalah |
| 2023 | Towards Robust Fairness-aware Recommendation. Hao Yang, Zhining Liu, Zeyu Zhang, Chenyi Zhuang, Xu Chen |
| 2023 | Towards Self-Explaining Sequence-Aware Recommendation. Alejandro Ariza-Casabona, Maria Salamó, Ludovico Boratto, Gianni Fenu |
| 2023 | Towards Sustainability-aware Recommender Systems: Analyzing the Trade-off Between Algorithms Performance and Carbon Footprint. Giuseppe Spillo, Allegra De Filippo, Cataldo Musto, Michela Milano, Giovanni Semeraro |
| 2023 | Track Mix Generation on Music Streaming Services using Transformers. Walid Bendada, Théo Bontempelli, Mathieu Morlon, Benjamin Chapus, Thibault Cador, Thomas Bouabça, Guillaume Salha-Galvan |
| 2023 | Transparently Serving the Public: Enhancing Public Service Media Values through Exploration. Andreas Grün, Xenija Neufeld |
| 2023 | Trending Now: Modeling Trend Recommendations. Hao Ding, Branislav Kveton, Yifei Ma, Youngsuk Park, Venkataramana Kini, Yupeng Gu, Ravi Divvela, Fei Wang, Anoop Deoras, Hao Wang |
| 2023 | Trustworthy Recommender Systems: Technical, Ethical, Legal, and Regulatory Perspectives. Markus Schedl, Vito Walter Anelli, Elisabeth Lex |
| 2023 | Turning Dross Into Gold Loss: is BERT4Rec really better than SASRec? Anton Klenitskiy, Alexey Vasilev |
| 2023 | Tutorial on Large Language Models for Recommendation. Wenyue Hua, Lei Li, Shuyuan Xu, Li Chen, Yongfeng Zhang |
| 2023 | Two-sided Calibration for Quality-aware Responsible Recommendation. Chenyang Wang, Yankai Liu, Yuanqing Yu, Weizhi Ma, Min Zhang, Yiqun Liu, Haitao Zeng, Junlan Feng, Chao Deng |
| 2023 | Uncertainty-adjusted Inductive Matrix Completion with Graph Neural Networks. Petr Kasalický, Antoine Ledent, Rodrigo Alves |
| 2023 | Uncovering ChatGPT's Capabilities in Recommender Systems. Sunhao Dai, Ninglu Shao, Haiyuan Zhao, Weijie Yu, Zihua Si, Chen Xu, Zhongxiang Sun, Xiao Zhang, Jun Xu |
| 2023 | Uncovering User Interest from Biased and Noised Watch Time in Video Recommendation. Haiyuan Zhao, Lei Zhang, Jun Xu, Guohao Cai, Zhenhua Dong, Ji-Rong Wen |
| 2023 | Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation. Yunzhu Pan, Chen Gao, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Depeng Jin, Yong Li |
| 2023 | Unleash the Power of Context: Enhancing Large-Scale Recommender Systems with Context-Based Prediction Models. Jan Hartman, Assaf Klein, Davorin Kopic, Natalia Silberstein |
| 2023 | User Behavior Modeling with Deep Learning for Recommendation: Recent Advances. Weiwen Liu, Wei Guo, Yong Liu, Ruiming Tang, Hao Wang |
| 2023 | User-Centric Conversational Recommendation: Adapting the Need of User with Large Language Models. Gangyi Zhang |
| 2023 | Using Learnable Physics for Real-Time Exercise Form Recommendations. Abhishek Jaiswal, Gautam Chauhan, Nisheeth Srivastava |
| 2023 | VideoRecSys 2023: First Workshop on Large-Scale Video Recommender Systems. Khushhall Chandra Mahajan, Amey Porobo Dharwadker, Saurabh Gupta, Brad Schumitsch |
| 2023 | Visual Representation for Capturing Creator Theme in Brand-Creator Marketplace. Sarel Duanis, Keren Gaiger, Ravid Cohen, Shaked Zychlinski, Asnat Greenstein-Messica |
| 2023 | What We Evaluate When We Evaluate Recommender Systems: Understanding Recommender Systems' Performance using Item Response Theory. Yang Liu, Alan Medlar, Dorota Glowacka |
| 2023 | When Fairness meets Bias: a Debiased Framework for Fairness aware Top-N Recommendation. Jiakai Tang, Shiqi Shen, Zhipeng Wang, Zhi Gong, Jingsen Zhang, Xu Chen |
| 2023 | Widespread Flaws in Offline Evaluation of Recommender Systems. Balázs Hidasi, Ádám Tibor Czapp |
| 2023 | Workshop on Context-Aware Recommender Systems 2023. Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Alexander Tuzhilin, Moshe Unger |
| 2023 | Workshop on Learning and Evaluating Recommendations with Impressions (LERI). Maurizio Ferrari Dacrema, Pablo Castells, Justin Basilico, Paolo Cremonesi |
| 2023 | Workshop on Recommenders in Tourism (RecTour) 2023. Julia Neidhardt, Wolfgang Wörndl, Tsvi Kuflik, Dmitri Goldenberg, Markus Zanker |
| 2023 | gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling. Aleksandr Vladimirovich Petrov, Craig Macdonald |
| 2023 | ✨ Going Beyond Local: Global Graph-Enhanced Personalized News Recommendations. Boming Yang, Dairui Liu, Toyotaro Suzumura, Ruihai Dong, Irene Li |