Hub Library
How to Access Recordings
Recordings for tutorials and paper sessions will be available here in the library 24 to 48 hours after the end of the session and will be available until December 15, 2023.
A Framework and Toolkit for Testing the Correctness of Recommendation Algorithms
Lien Michiels, Robin Verachtert, Andres Ferraro, Kim Falk and Bart Goethals
Live Session
A Lightweight Method for Modeling Confidence in Recommendations with Learned Beta Distributions
Norman Knyazev and Harrie Oosterhuis
Live Session
A Model-Agnostic Framework for Recommendation via Interest-aware Item Embeddings
Amit Kumar Jaiswal (University of Surrey) and Yu Xiong (University of Surrey).
Live Session
A Multi-view Graph Contrastive Learning Framework for Cross-Domain Sequential Recommendation
Zitao Xu (Shenzhen University), Weike Pan (Shenzhen University) and Zhong Ming (Shenzhen University)
Live Session
A Probabilistic Position Bias Model for Short-Video Recommendation Feeds
Olivier Jeunen (ShareChat)
Live Session
ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction
Haoxuan Li (Center for Data Science, Peking University), Taojun Hu (Peking University), Zetong Xiong (Zhongnan University of Economic and Law), Chunyuan Zheng (University of California, San Diego), Fuli Feng (University of Science and Technology of China), Xiangnan He (University of Science and Technology of China) and Xiao-Hua Zhou (Peking University)
Live Session
Accelerating Creator Audience Building through Centralized Exploration
Buket Baran (Spotify), Guilherme Dinis Junior (Spotify), Antonina Danylenko (Spotify), Olayinka S. Folorunso (Spotify), Gösta Forsum (Spotify), Maksym Lefarov (Spotify), Lucas Maystre (Spotify) and Yu Zhao (Spotify)
Live Session
Acknowledging dynamic aspects of trust in recommender systems
Imane Akdim (School of Computer Science – Mohammed VI Polytechnic University).
Live Session
AdaptEx: a self-service contextual bandit platform
PLEASE NOTE: The AdaptEx recording will not be available due to privacy requirements of the authors' employer. Thank you for your understanding.
William Black (Expedia Group), Ercument Ilhan (Expedia Group), Andrea Marchini (Expedia Group) and Vilda Markeviciute (Expedia Group)
Live Session
Adaptive Collaborative Filtering with Personalized Time Decay Functions for Financial Product Recommendation
Ashraf Ghiye (École Polytechnique), Baptiste Barreau (BNP Paribas CIB – Global Markets), Laurent Carlier (BNP Paribas CIB – Global Markets) and Michalis Vazirgiannis (École Polytechnique).
Live Session
Advancing Automation of Design Decisions in Recommender System Pipelines
Tobias Vente (University of Siegen).
Live Session
Adversarial Collaborative Filtering for Free
Huiyuan Chen (Visa Research), Xiaoting Li (Visa Research), Vivian Lai (Visa Research), Chin-Chia Michael Yeh (Visa Research), Yujie Fan (Visa Research), Yan Zheng (Visa Research), Mahashweta Das (Visa Research) and Hao Yang (Visa Research).
Live Session
Adversarial Sleeping Bandit Problems with Multiple Plays: Algorithm and Ranking Application
Jianjun Yuan (Expedia Group), Wei Lee Woon (Expedia Group) and Ludovik Coba (Expedia Group)
Live Session
Alleviating the Long-Tail Problem in Conversational Recommender Systems
Zhipeng Zhao (Singapore Management University), Kun Zhou (School of Information, Renmin University of China), Xiaolei Wang (Gaoling School of Artificial Intelligence, Renmin University of China), Wayne Xin Zhao (Gaoling School of Artificial Intelligence, Renmin University of China), Fan Pan (Poisson Lab, Huawei), Zhao Cao (Poisson Lab, Huawei) and Ji-Rong Wen (Gaoling School of Artificial Intelligence, Renmin University of China)
Live Session
An Exploration of Sentence-Pair Classification for Algorithmic Recruiting
Mesut Kaya (Aalborg University Copenhagen) and Toine Bogers (IT University of Copenhagen).
Live Session
An Industrial Framework for Personalized Serendipitous Recommendation in E-commerce
Zongyi Wang (jd.com), Yanyan Zou (JD.com), Anyu Dai (jd.com), Linfang Hou (jd.com), Nan Qiao (jd.com), Luobao Zou (jd.com), Mian Ma (JD.com), Zhuoye Ding (JD.com) and Sulong Xu (JD)
Live Session
Analysis Operations for Constraint-based Recommender Systems
Sebastian Lubos (Institute of Software Technology – Graz University of Technology), Viet-Man Le (Graz University of Technology), Alexander Felfernig (TU Graz) and Thi Ngoc Trang Tran (Graz University of Technology)
Live Session
Analyzing Accuracy versus Diversity in a Health Recommender System for Physical Activities: a Longitudinal User Study
Ine Coppens (WAVES – imec – Ghent University), Luc Martens (WAVES – imec – Ghent University) and Toon De Pessemier (WAVES – imec – Ghent University).
Live Session
Augmented Negative Sampling for Collaborative Filtering
Yuhan Zhao (Harbin Engineering University), Rui Chen (Harbin Engineering University), Riwei Lai (Harbin Engineering University), Qilong Han (Harbin Engineering University), Hongtao Song (Harbin Engineering University) and Li Chen (Hong Kong Baptist University)
Live Session
AutoOpt: Automatic Hyperparameter Scheduling and Optimization for Deep Click-through Rate Prediction
Yujun Li (Noah’s Ark Lab), Xing Tang (Noah’s Ark Lab), Bo Chen (Noah’s Ark Lab), Yimin Huang (Noah’s Ark Lab), Ruiming Tang (Noah’s Ark Lab) and Zhenguo Li (Noah’s Ark Lab)
Live Session
BVAE: Behavior-aware Variational Autoencoder for Multi-Behavior Multi-Task Recommendation
Qianzhen Rao (Shenzhen University), Yang Liu (Shenzhen University), Weike Pan (Shenzhen University) and Zhong Ming (Shenzhen University)
Live Session
Beyond Labels: Leveraging Deep Learning and LLMs for Content Metadata
Saurabh Agrawal (Tubi), John Trenkle (Tubi) and Jaya Kawale (Tubi)
Live Session
Beyond the Sequence: Statistics-driven Pre-training for Stabilizing Sequential Recommendation Model
Sirui Wang (Meituan Group), Peiguang Li (Meituan Group), Yunsen Xian (Meituan Group) and Hongzhi Zhang (Meituan Group)
Live Session
Bootstrapped Personalized Popularity for Cold Start Recommender Systems
Jason Chaimalas (University College London), Duncan Walker (British Broadcasting Corporation), Edoardo Gruppi (University College London), Ben Clark (British Broadcasting Corporation) and Laura Toni (University College London).
Live Session
Broadening the Scope: Evaluating the Potential of Recommender Systems beyond prioritizing Accuracy
Vincenzo Paparella (Politecnico di Bari), Dario Di Palma (Politecnico di Bari), Vito Walter Anelli (Politecnico di Bari) and Tommaso Di Noia (Politecnico di Bari).
Live Session
CR-SoRec: BERT driven Consistency Regularization for Social Recommendation
Tushar Prakash (Sony Research India), Raksha Jalan (Sony Research india), Brijraj Singh (Sony Research india) and Naoyuki Onoe (Sony).
Live Session
Can ChatGPT Make Fair Recommendation? A Fairness Evaluation Benchmark for Recommendation with Large Language Model
Jizhi Zhang (University of Science and Technology of China), Keqin Bao (University of Science and Technology of China), Yang Zhang (University of Science and Technology of China), Wenjie Wang (National University of Singapore), Fuli Feng (University of Science and Technology of China) and Xiangnan He (University of Science and Technology of China).
Live Session
Challenges for Anonymous Session-Based Recommender Systems in Indoor Environments
Alessio Ferrato (Roma TRE).
Live Session
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis
Vito Walter Anelli (Politecnico di Bari), Daniele Malitesta (Polytechnic University of Bari), Claudio Pomo (Politecnico di Bari), Alejandro Bellogin (Universidad Autonoma de Madrid), Eugenio Di Sciascio (Politecnico di Bari) and Tommaso Di Noia (Politecnico di Bari)
Live Session
Climbing crags repetitive choices and recommendations
Iustina Ivanova (Independent Researcher).
Live Session
Closing Remarks and 2024 Reveal
Live Session
Co-occurrence Embedding Enhancement for Long-tail Problem in Multi-Interest Recommendation
Yaokun Liu (Tianjin University), Xiaowang Zhang (Tianjin University), Minghui Zou (Tianjin University) and Zhiyong Feng (Tianjin University).
Live Session
Collaborative filtering algorithms are prone to mainstream-taste bias
Pantelis Analytis (University of Southern Denmark) and Philipp Hager (University of Amsterdam)
Live Session
Complementary Product Recommendation for Long-tail Products
Rastislav Papso (Kempelen Institute of Intelligent Technologies)
Live Session
Contextual Multi-Armed Bandit for Email Layout Recommendation
Yan Chen (Wayfair), Emilian Vankov (Wayfair), Linas Baltrunas (Netflix), Preston Donovan (Wayfair), Akash Mehta (Wayfair) and Benjamin Schroeder (Wayfair)
Live Session
Continual Collaborative Filtering Through Gradient Alignment
Hieu Do (Singapore Management University) and Hady Lauw (Singapore Management University).
Live Session
Contrastive Learning with Frequency-Domain Interest Trends for Sequential Recommendation
Yichi Zhang (Harbin Engineering University), Guisheng Yin (Harbin Engineering University) and Yuxin Dong (Harbin Engineering University)
Live Session
Correcting for Interference in Experiments: A Case Study at Douyin
Vivek Farias (MIT), Hao Li (Bytedance), Tianyi Peng (MIT), Xinyuyang Ren (Bytedance), Huawei Zhang (Bytedance) and Andrew Zheng (MIT)
Live Session
Creating the next generation of news experience at ekstrabladet.dk with recommender systems
ohannes Kruse (DTU Compute & Ekstra Bladet), Kasper Lindskow (Ekstra Bladet), Michael Riis Andersen (DTU Compute) and Jes Frellsen (DTU Compute).
Live Session
DREAM: Decoupled Representation via Extraction Attention Module and Supervised Contrastive Learning for Cross-Domain Sequential Recommender
Xiaoxin Ye (School of Computer Science and Engineering, UNSW), Yun Li (School of Computer Science and Engineering, UNSW) and Lina Yao (CSIRO Data61, School of Computer Science and Engineering UNSW)
Live Session
DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation
Zhu Sun, Hui Fang, Jie Yang, Xinghua Qu, Hongyang Liu, Di Yi, Yew-Soon Ong and Jie Zhang
Live Session
Data-free Knowledge Distillation for Reusing Recommendation Models
Cheng Wang (Huazhong University of Science and Technology), Jiacheng Sun (Huawei Noah’s Ark Lab), Zhenhua Dong (Huawei Noah’s Ark Lab), Jieming Zhu (Huawei Noah’s Ark Lab), Zhenguo Li (Huawei Noah’s Ark Lab), Ruixuan Li (Huazhong University of Science and Technology) and Rui Zhang (ruizhang.info)
Live Session
Deep Exploration for Recommendation Systems
Zheqing Zhu (Meta AI, Stanford University) and Benjamin Van Roy (Stanford University).
Live Session
Deep Situation-Aware Interaction Network for Click-Through Rate Prediction
Yimin Lv (Institute of Software, Chinese Academy of Sciences), Shuli Wang (Meituan), Beihong Jin (Institute of Software, Chinese Academy of Sciences), Yisong Yu (Institute of Software, Chinese Academy of Sciences), Yapeng Zhang (Meituan), Jian Dong (Meituan), Yongkang Wang (Meituan), Xingxing Wang (Meituan) and Dong Wang (Meituan)
Live Session
Deliberative Diversity for News Recommendations: Operationalization and Experimental User Study
Lucien Heitz (University of Zurich), Juliane A. Lischka (University of Hamburg), Rana Abdullah (University of Hamburg), Laura Laugwitz (University of Hamburg), Hendrik Meyer (University of Hamburg) and Abraham Bernstein (University of Zurich).
Live Session
Delivery Hero Recommendation Dataset: A Novel Dataset for Benchmarking Recommendation Algorithms
Yernat Assylbekov (Delivery Hero), Raghav Bali (Delivery Hero), Luke Bovard (Delivery Hero) and Christian Klaue (Delivery Hero).
Live Session
Demystifying Recommender Systems: A Multi-faceted Examination of Explanation Generation, Impact, and Perception
Giacomo Balloccu (Università degli Studi di Cagliari).
Live Session
Denoising Explicit Social Signals for Robust Recommendation
Youchen Sun (Nanyang Technological University).
Live Session
Disentangling Motives behind Item Consumption and Social Connection for Mutually-enhanced Joint Prediction
Youchen Sun (Nanyang Technological University), Zhu Sun (A*STAR), Xiao Sha (Nanyang Technological University), Jie Zhang (Nanyang Technological University) and Yew Soon Ong (Nanyang Technological University)
Live Session
Distribution-based Learnable Filters with Side Information for Sequential Recommendation
Haibo Liu (School of Cyber Security and Computer, HeBei university), Zhixiang Deng (School of Cyber Security and Computer, HeBei university), Liang Wang (School of Cyber Security and Computer, HeBei university), Jinjia Peng (School of Cyber Security and Computer, HeBei university) and Shi Feng (School of Computer Science & Engineering, Northeastern University)
Live Session
Domain Disentanglement with Interpolative Data Augmentation for Dual-Target Cross-Domain Recommendation
Jiajie Zhu (Macquarie University), Yan Wang (Macquarie University), Feng Zhu (Ant Group) and Zhu Sun (Macquarie University)
Live Session
EasyStudy: Framework for Easy Deployment of User Studies on Recommender Systems
Patrik Dokoupil (Department of Software Engineering, Charles University) and Ladislav Peska (Faculty of Mathematics and Physics, Charles University, Prague, Czechia)
Live Session
Effects of Personalized Recommendations versus Aggregate Ratings on Post-Consumption Preference Responses
Gediminas Adomavicius, Jesse Bockstedt, Shawn Curley and Jingjing Zhang
Live Session
Efficient Data Representation Learning in Google-scale Systems
Derek Cheng (Google DeepMind), Ruoxi Wang (Google DeepMind), Wang-Cheng Kang (Google DeepMind), Benjamin Coleman (Google DeepMind), Yin Zhang (Google DeepMind), Jianmo Ni (Google DeepMind), Jonathan Valverde (Google DeepMind), Lichan Hong (Google DeepMind) and Ed Chi (Google DeepMind)
Live Session
Enhanced Privacy Preservation for Recommender Systems
Ziqing Wu (NTU).
Live Session
Enhancing Transformer without Self-supervised Learning: A Loss Landscape Perspective in Sequential Recommendation
Vivian Lai (Visa Research), Huiyuan Chen (Visa Research), Chin-Chia Michael Yeh (Visa Research), Minghua Xu (Visa Research), Yiwei Cai (Visa Research) and Hao Yang (Visa Research).
Live Session
Equivariant Contrastive Learning for Sequential Recommendation
Peilin Zhou (HKUST (Guangzhou)), Jingqi Gao (Upstage), Yueqi Xie (HKUST), Qichen Ye (Peking University), Yining Hua (Harvard Medical School), Jaeboum Kim (The University of Hong Kong Science and Technology, Upstage), Shoujin Wang (Data Science Institute, University of Technology Sydney) and Sunghun Kim (The University of Hong Kong Science and Technology)
Live Session
Evaluating Recommender Systems: Survey and Framework
Eva Zangerle and Christine Bauer
Live Session
Evaluating The Effects of Calibrated Popularity Bias Mitigation: A Field Study
Anastasiia Klimashevskaia (MediaFutures, University of Bergen), Mehdi Elahi (MediaFutures, University of Bergen), Dietmar Jannach (University of Klagenfurt), Lars Skjærven (TV 2), Astrid Tessem (TV 2) and Christoph Trattner (MediaFutures, University of Bergen)
Live Session
Everyone's a Winner! On Hyperparameter Tuning of Recommendation Models
Faisal Shehzad (University of Klagenfurt) and Dietmar Jannach (University of Klagenfurt)
Live Session
Ex2Vec: Characterizing Users and Items from the Mere Exposure Effect
Bruno Sguerra (Deezer Research) and Romain Hennequin (Deezer Research).
Live Session
Explainable Graph Neural Network Recommenders; Challenges and Opportunities
Amir Reza Mohammadi (Universität Innsbruck)
Live Session
Exploring False Hard Negative Sample in Cross-Domain Recommendation
Haokai Ma (Shandong University), Ruobing Xie (WeChat, Tencent), Lei Meng (School of software, Shandong University), Xin Chen (tencent), Xu Zhang (WeChat Search Application Department, Tencent Inc.), Leyu Lin (WeChat Search Application Department, Tencent) and Jie Zhou (Wechat, Tencent)
Live Session
Exploring Unlearning Methods to Ensure the Privacy, Security, and Usability of Recommender Systems
Jens Leysen (University of Antwerp)
Live Session
Extended conversion: Capturing successful interactions in voice shopping
Elad Haramaty (Amazon), Zohar Karnin (Amazon), Arnon Lazerson (Amazon), Liane Lewin-Eytan (Amazon Research) and Yoelle Maarek (Amazon).
Live Session
Fast and Examination-agnostic Reciprocal Recommendation in Matching Markets
Yoji Tomita (CyberAgent, Inc.), Riku Togashi (CyberAgent, Inc.), Yuriko Hashizume (CyberAgent, Inc.) and Naoto Ohsaka (CyberAgent, Inc.)
Live Session
From Research to Production: Towards Scalable and Sustainable Neural Recommendation Models on Commodity CPU Hardware
Vihan Lakshman (ThirdAI), Anshumali Shrivastava (Rice University/ThirdAI), Tharun Medini (ThirdAI), Nicholas Meisburger (ThirdAI Corp), Joshua Engels (ThirdAI), David Torres Ramos (ThirdAI), Benito Geordie (ThirdAI), Pratik Pranav (ThirdAI), Shubh Gupta (ThirdAI), Yashwanth Adunukota (ThirdAI) and Siddharth Jain (ThirdAI).
Live Session
Full Index Deep Retrieval: End-to-End User and Item Structures for Cold-start and Long-tail Item Recommendation
Zhen Gong (Shanghai Jiao Tong University), Xin Wu (Bytedance Inc.), Lei Chen (Bytedance Inc.), Zhenzhe Zheng (Shanghai Jiao Tong University), Shengjie Wang (Bytedance Inc.), Anran Xu (Shanghai Jiao Tong University), Chong Wang (Bytedance Inc.) and Fan Wu (Shanghai Jiao Tong University)
Live Session
Generative Learning Plan Recommendation for Employees: A Performance-aware Reinforcement Learning Approach
Zhi Zheng (University of Science and Technology of China), Ying Sun (The Hong Kong University of Science and Technology (Guangzhou)), Xin Song (Baidu), Hengshu Zhu (BOSS Zhipin) and Hui Xiong (The Hong Kong University of Science and Technology (Guangzhou))
Live Session
Generative Next-Basket Recommendation
Wenqi Sun (Renmin University of China), Ruobing Xie (WeChat, Tencent), Junjie Zhang (Renmin University of China), Wayne Xin Zhao (Renmin University of China), Leyu Lin (WeChat Search Application Department, Tencent) and Ji-Rong Wen (Renmin University of China)
Live Session
Goal-Oriented Multi-Modal Interactive Recommendation with Verbal and Non-Verbal Relevance Feedback
Yaxiong Wu (University of Glasgow), Craig Macdonald (University of Glasgow) and Iadh Ounis (University of Glasgow
Live Session
Going Beyond Local: Global Graph-Enhanced Personalized News Recommendations
Boming Yang (The University of Tokyo), Dairui Liu (University College Dublin), Toyotaro Suzumura (The University of Tokyo), Ruihai Dong (University College Dublin) and Irene Li (The University of Tokyo)
Live Session
Gradient Matching for Categorical Data Distillation in CTR Prediction
Cheng Wang (School of Cyber Science and Engineering, Huazhong University of Science and Technology, Wuhan), Jiacheng Sun (Huawei Noah’s Ark Lab), Zhenhua Dong (Huawei Noah’s Ark Lab), Ruixuan Li (School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan) and Rui Zhang (ruizhang.info)
Live Session
Group Fairness for Content Creators: the Role of Human and Algorithmic Biases under Popularity-based Recommendations
Stefania Ionescu (University of Zurich), Aniko Hannak (University of Zurich) and Nicolo Pagan (UZH).
Live Session
HUMMUS: A Linked, Healthiness-Aware, User-centered and Argument-Enabling Recipe Data Set for Recommendation
Felix Bölz (INSA Lyon & University of Passau), Diana Nurbakova (INSA Lyon), Sylvie Calabretto (INSA Lyon), Armin Gerl (University of Passau), Lionel Brunie (INSA Lyon) and Harald Kosch (University of Passau)
Live Session
Hessian-aware Quantized Node Embeddings for Recommendation
Huiyuan Chen (Visa Research), Kaixiong Zhou (Rice University), Kwei-Herng Lai (Rice University), Chin-Chia Michael Yeh (Visa Research), Yan Zheng (Visa Research), Xia Hu (Rice University) and Hao Yang (Visa Research)
Live Session
Heterogeneous Knowledge Fusion: A Novel Approach for Personalized Recommendation via LLM
Bin Yin (Meituan), Junjie Xie (Meituan), Yu Qin (Meituan), Zixiang Ding (Meituan), Zhichao Feng (Meituan), Xiang Li (Unaffiliated) and Wei Lin (Unaffiliated)
Live Session
How Should We Measure Filter Bubbles? A Regression Model and Evidence for Online News
Lien Michiels (UAntwerpen), Jorre Vannieuwenhuyze (Statistiek Vlaanderen), Jens Leysen (University of Antwerp), Robin Verachtert (Froomle NV), Annelien Smets (imec-SMIT, Vrije Universiteit Brussel) and Bart Goethals (University of Antwerp)
Live Session
How Users Ride the Carousel: Exploring the Design of Multi-List Recommender Interfaces From a User Perspective
Benedikt Loepp (University of Duisburg-Essen) and Jürgen Ziegler (University of Duisburg-Essen)
Live Session
Identifying Controversial Pairs in Item-to-Item Recommendations
Junyi Shen (Apple), Dayvid Rodrigues de Oliveira (Apple), Jin Cao (Apple), Brian Knott (Apple), Goodman Gu (Apple), Sindhu Vijaya Raghavan (Apple) and Rob Monarch (Apple)
Live Session
Improving Group Recommendations using Personality, Dynamic Clustering and Multi-Agent MicroServices
Patrícia Alves (GECAD/LASI – ISEP, Polytechnic of Porto), André Martins (GECAD/LASI – ISEP, Polytechnic of Porto), Paulo Novais (ALGORITMI/LASI, University of Minho) and Goreti Marreiros (GECAD/LASI, ISEP, Polytechnic of Porto).
Live Session
Improving Recommender Systems Through the Automation of Design Decisions
Lukas Wegmeth (University of Siegen).
Live Session
InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models
Kabir Nagrecha (University of California, San Diego), Lingyi Liu (Netflix, Inc.), Pablo Delgado (Netflix, Inc.) and Prasanna Padmanabhan (Netflix, Inc.)
Live Session
Incentivizing Exploration in Linear Bandits under Information Gap
Huazheng Wang (Oregon State University), Haifeng Xu (University of Chicago), Chuanhao Li (University of Virginia), Zhiyuan Liu (University of colorado,boulder) and Hongning Wang (University of Virginia)
Live Session
Incorporating Time in Sequential Recommendation Models
Mostafa Rahmani (Amazon), James Caverlee (Amazon) and Fei Wang (Amazon).
Live Session
Initiative transfer in conversational recommender systems
Yuan Ma (University of Duisburg-Essen) and Jürgen Ziegler (University of Duisburg-Essen).
Live Session
Integrating Item Relevance in Training Loss for Sequential Recommender Systems
Andrea Bacciu (Sapienza University of Rome), Federico Siciliano (Sapienza University of Rome), Nicola Tonellotto (University of Pisa) and Fabrizio Silvestri (University of Rome)
Live Session
Integrating Offline Reinforcement Learning with Transformers for Sequential Recommendation
Xumei Xi (Cornell University), Yuke Zhao (Bloomberg LP), Quan Liu (Bloomberg), Liwen Ouyang (Bloomberg) and Yang Wu (Independent Researcher)
Live Session
Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation
Marta Moscati (Johannes Kepler University Linz), Christian Wallmann (Johannes Kepler University Linz), Markus Reiter-Haas (Graz University of Technology), Dominik Kowald (Know-Center GmbH and Graz University of Technology), Elisabeth Lex (Graz University of Technology) and Markus Schedl (Johannes Kepler University Linz)
Live Session
Interface Design to Mitigate Inflation in Recommender Systems
Rana Shahout (Technion), Yehonatan Peisakhovsky (Technion), Sasha Stoikov (Cornell Tech) and Nikhil Garg (Cornell Tech).
Live Session
Interpretable User Retention Modeling in Recommendation
Rui Ding (Northeastern University), Ruobing Xie (WeChat, Tencent), Xiaobo Hao (WeChat, Tencent), Xiaochun Yang (Northeastern University), Kaikai Ge (WeChat, Tencent), Xu Zhang (WeChat, Tencent), Jie Zhou (WeChat, Tencent) and Leyu Lin (WeChat, Tencent).
Live Session
Introducing LensKit-Auto, an Experimental Automated Recommender System (AutoRecSys) Toolkit
Tobias Vente (University of Siegen), Michael Ekstrand (Boise State University) and Joeran Beel (University of Siegen).
Live Session
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 and Chris Green
Live Session
KGTORe: Tailored Recommendations through Knowledge-aware GNN Models
Alberto Carlo Maria Mancino (Politecnico di Bari), Antonio Ferrara (Politecnico di Bari), Salvatore Bufi (Polytechnic University of Bari), Daniele Malitesta (Polytechnic University of Bari), Tommaso Di Noia (Polytechnic University of Bari) and Eugenio Di Sciascio (Polytechnic University of Bari)
Live Session
Keynote: From Documents to Dialogues: How LLMs are Shaping the Future of Work
Jaime Teevan
Live Session
Keynote: Recommendation systems: Challenges and solutions
Rajeev Rastogi
Live Session
Keynote: Towards Generative Search and Recommendation
Tat-Seng Chua
Live Session
Knowledge-Aware Recommender Systems based on Multi-Modal Information Sources
Giuseppe Spillo (University of Bari ‘Aldo Moro’)
Live Session
Knowledge-based Multiple Adaptive Spaces Fusion for Recommendation
Meng Yuan (Institute of Artificial Intelligence, Beihang University, Beijing 100191, China), Fuzhen Zhuang (Institute of Artificial Intelligence, Beihang University, Beijing 100191, China), Zhao Zhang (University of Chinese Academy of Sciences, Beijing 100191, China), Deqing Wang (School of Computer Science and Engineering, Beihang University, Beijing 100191, China) and Jin Dong (Beijing Academy of Blockchain and Edge Computing)
Live Session
LLM Based Generation of Item-Description for Recommendation System
Arkadeep Acharya (Sony Research India), Brijraj Singh (Sony Research India) and Naoyuki Onoe (Sony Research India).
Live Session
LLM4Rec: Large Language Models for Recommendation via A Lightweight Tuning Framework
Keqin Bao (University of Science and Technology in China), Jizhi Zhang (University of Science and Technology in China), Yang Zhang (University of Science and Technology of China), Wenjie Wang (National University of Singapore), Fuli Feng (University of Science and Technology in China) and Xiangnan He (University of Science and Technology of China).
Live Session
Large Language Model Augmented Narrative Driven Recommendations
Sheshera Mysore (University of Massachusetts Amherst), Andrew Mccallum (University of Massachusetts) and Hamed Zamani (University of Massachusetts Amherst)
Live Session
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences
Scott Sanner (Google), Krisztian Balog (Google), Filip Radlinski (Google), Ben Wedin (Google) and Lucas Dixon (Google).
Live Session
Learning From Negative User Feedback and Measuring Responsiveness for Sequential Recommenders
Yueqi Wang (Google), Yoni Halpern (Google), Shuo Chang (Google), Jingchen Feng (Google), Elaine Ya Le (Google), Longfei Li (Google), Xujian Liang (Google), Min-Cheng Huang (Google), Shane Li (Google), Alex Beutel (Google), Yaping Zhang (Google) and Shuchao Bi (Google).
Live Session
Learning the True Objectives of Multiple Tasks in Sequential Behavior Modeling
Jiawei Zhang (Peking University)
Live Session
Leveling Up the Peloton Homescreen: A System and Algorithm for Dynamic Row Ranking
Natalia Chen (Peloton Interactive), Nganba Meetei (Peloton Interactive), Nilothpal Talukder (Peloton Interactive) and Alexey Zankevich (Peloton Interactive).
Live Session
Leveraging Large Language Models for Sequential Recommendation
Jesse Harte (Delivery Hero SE), Wouter Zorgdrager (Delivery Hero SE), Panos Louridas (Athens University of Economics & Business), Asterios Katsifodimos (Delft University of Technology), Dietmar Jannach (University of Klagenfurt) and Marios Fragkoulis (Delivery Hero SE)
Live Session
LightSAGE: Graph Neural Networks for Large Scale Item Retrieval in Shopee’s Advertisement Recommendation
Dang Minh Nguyen (Shopee, SEA Group), Chenfei Wang (Shopee, SEA Group), Yan Shen (Shopee, SEA Group) and Yifan Zeng (Shopee, SEA Group)
Live Session
Localify.org: Locally-focus Music Artist and Event Recommendation
Douglas Turnbull (Ithaca College), April Trainor (Ithaca College), Griffin Homan (Ithaca College), Elizabeth Richards (Ithaca College), Kieran Bentley (Ithaca College), Victoria Conrad (Ithaca College), Paul Gagliano (Ithaca College) and Cassandra Raineault (Ithaca College)
Live Session
Looks Can Be Deceiving: Linking User-Item Interactions and User's Propensity Towards Multi-Objective Recommendations
Patrik Dokoupil (Department of Software Engineering, Charles University), Ladislav Peska (Faculty of Mathematics and Physics, Charles University, Prague, Czechia) and Ludovico Boratto (University of Cagliari).
Live Session
Loss Harmonizing for Multi-Scenario CTR Prediction
Congcong Liu (JD.com), Liang Shi (JD.com), Pei Wang (JD.com), Fei Teng (JD.com), Xue Jiang (JD.com), Changping Peng (JD.com), Zhangang Lin (JD.com) and Jingping Shao (JD.com)
Live Session
M3REC: A Meta-based Multi-scenario Multi-task Recommendation Framework
Zerong Lan (Dalian University of Technology), Yingyi Zhang (Dalian University of technology) and Xianneng Li (Dalian University of Technology)
Live Session
MLCM: A Multi-task Large Pre-trained Customer Model for Personalization
Rui Luo (Amazon), Tianxin Wang (Amazon), Jingyuan Deng (Amazon) and Peng Wan (Amazon)
Live Session
Masked and Swapped Sequence Modeling for Next Novel Basket Recommendation in Grocery Shopping
Ming Li (University of Amsterdam), Mozhdeh Ariannezhad (University of Amsterdam), Andrew Yates (University of Amsterdam) and Maarten de Rijke (University of Amsterdam)
Live Session
Multi-Relational Contrastive Learning for Recommendation
Wei Wei (University of Hong Kong), Lianghao Xia (University of Hong Kong) and Chao Huang (University of Hong Kong)
Live Session
Multi-task Item-attribute Graph Pre-training for Strict Cold-start Item Recommendation
Yuwei Cao (University of Illinois at Chicago), Liangwei Yang (University of Illinois Chicago), Chen Wang (University of Illinois Chicago), Zhiwei Liu (Salesforce Inc.), Hao Peng (Beihang University), Chenyu You (Yale University) and Philip Yu (University of Illinois Chicago).
Live Session
Multiple Connectivity Views for Session-based Recommendation
Yaming Yang (School of Artificial Intelligence, Peking University), Jieyu Zhang (University of Washington), Yujing Wang (School of Artificial Intelligence, Peking University), Zheng Miao (School of Artificial Intelligence, Peking University) and Yunhai Tong (Peking University).
Live Session
Navigating the Feedback Loop in Recommender Systems: Insights and Strategies from Industry Practice
Ding Tong (Netflix), Qifeng Qiao (Netflix), Ting-Po Lee (Netflix), James McInerney (Netflix) and Justin Basilico (Netflix).
Live Session
Nonlinear Bandits Exploration for Recommendations
Yi Su (Google) and Minmin Chen (Google).
Live Session
Of Spiky SVDs and Music Recommendation
Darius Afchar (Deezer Research), Romain Hennequin (Deezer Research) and Vincent Guigue (AgroParisTech).
Live Session
On the Consistency of Average Embeddings for Item Recommendation
Walid Bendada (Deezer Research & LAMSADE, Université Paris Dauphine – PSL), Guillaume Salha-Galvan (Deezer Research), Romain Hennequin (Deezer Research), Thomas Bouabça (Deezer Research) and Tristan Cazenave (LAMSADE Université Paris Dauphine PSL – CNRS)
Live Session
On the Consistency, Discriminative Power and Robustness of Sampled Metrics in Offline Top-N Recommender System Evaluation
Yang Liu (University of Helsinki), Alan Medlar (University of Helsinki) and Dorota Glowacka (University of Helsinki).
Live Session
Online Matching: A Real-time Bandit System for Large-scale Recommendations
Xinyang Yi (Google), Shao-Chuan Wang (Google), Ruining He (Google), Hariharan Chandrasekaran (Google), Charles Wu (Google), Lukasz Heldt (Google), Lichan Hong (Google), Minmin Chen (Google) and Ed Chi (Google).
Live Session
Optimizing Long-term Value for Auction-Based Recommender Systems via On-Policy Reinforcement Learning
Ruiyang Xu (Meta AI), Jalaj Bhandari (Meta AI), Dmytro Korenkevych (Meta AI), Fan Liu (Meta), Yuchen He (Meta), Alex Nikulkov (Meta AI) and Zheqing Zhu (Meta AI)
Live Session
Optimizing Podcast Discovery: Unveiling Amazon Music's Retrieval and Ranking Framework
Geetha Aluri (Amazon), Paul Greyson (Amazon) and Joaquin Delgado (Amazon).
Live Session
OutRank: Speeding up AutoML-based Model Search for Large Sparse Data sets with Cardinality-aware Feature Ranking
Blaž Škrlj (Outbrain) and Blaž Mramor (Outbrain).
Live Session
Overcoming Recommendation Limitations with Neuro-Symbolic Integration
Tommaso Carraro (University of Padova / Fondazione Bruno Kessler).
Live Session
Pairwise Intent Graph Embedding Learning for Context-Aware Recommendation
Dugang Liu (Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)), Yuhao Wu (Shenzhen University), Weixin Li (Shenzhen University), Xiaolian Zhang (Huawei 2012 Lab), Hao Wang (Huawei 2012 Lab), Qinjuan Yang (Huawei 2012 Lab) and Zhong Ming (College of Computer Science and Software Engineering, Shenzhen University)
Live Session
Personalised Recommendations for the BBC iPlayer: Initial approach and current challenges
Benjamin R. Clark (British Broadcasting Corporation), Kristine Grivcova (British Broadcasting Corporation), Polina Proutskova (British Broadcasting Corporation) and Duncan M. Walker (British Broadcasting Corporation)
Live Session
Personalized Category Frequency prediction for Buy It Again recommendations
Amit Pande (Target), Kunal Ghosh (Target) and Rankyung Park (Target)
Live Session
Power Loss Function in Neural Networks for Predicting Click-Through Rate
Ergun Biçici (Huawei R&D Center Turkey).
Live Session
Private Matrix Factorization with Public Item Features
Mihaela Curmei (University of California, Berkeley), Walid Krichene (Google Research) and Li Zhang (Google Research).
Live Session
Progressive Horizon Learning: Adaptive Long Term Optimization for Personalized Recommendation
Congrui Yi (Amazon), David Zumwalt (Amazon), Zijian Ni (Amazon) and Shreya Chakrabarti (Amazon).
Live Session
Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders
Bjørnar Vassøy (Norwegian University of Science and Technology (NTNU)), Helge Langseth (Norwegian University of Science and Technology (NTNU)) and Benjamin Kille (Norwegian University of Science and Technology (NTNU)).
Live Session
Psychology-informed Recommender Systems
Elisabeth Lex, Dominik Kowald, Paul Seitlinger, Thi Ngoc Trang Tran, Alexander Felfernig and Markus Schedl
Live Session
Re2Dan: Retrieval of medical documents for e-Health in Danish
Antonela Tommasel (ISISTAN Research Institute, CONICET-UNCPBA), Rafael Pablos (Aarhus Universitet) and Ira Assent (Aarhus Universitet).
Live Session
ReCon: Reducing Congestion in Job Recommendation using Optimal Transport
Yoosof Mashayekhi (Ghent University), Bo Kang (Ghent University), Jefrey Lijffijt (Ghent University) and Tijl de Bie (Ghent University)
Live Session
RecAD : Towards A Unified Library for Recommender Attack and Defense
Changsheng Wang (University of Science and Technology of China), Jianbai Ye (University of Science and Technology of China), Wenjie Wang (National University of Singapore), Chongming Gao (University of Science and Technology of China), Fuli Feng (University of Science and Technology of China) and Xiangnan He (University of Science and Technology of China)
Live Session
RecQR: Using Recommendation Systems for Query Reformulation to correct unseen errors in spoken dialog systems
Manik Bhandari (Amazon.com), Mingxian Wang (Amazon), Oleg Poliannikov (Amazon) and Kanna Shimizu (Amazon)
Live Session
RecSys Opening
Live Session
Reciprocal Sequential Recommendation
Bowen Zheng (Renmin University of China), Yupeng Hou (Renmin University of China), Wayne Xin Zhao (Renmin University of China), Yang Song (BOSS Zhipin) and Hengshu Zhu (BOSS Zhipin)
Live Session
Reproducibility Analysis of Recommender Systems relying on Visual Features: traps, pitfalls, and countermeasures
Pasquale Lops (University of Bari), Elio Musacchio (Università degli Studi di Bari Aldo Moro), Cataldo Musto (Dipartimento di Informatica – University of Bari), Marco Polignano (Università degli Studi di Bari Aldo Moro), Antonio Silletti (Dipartimento di Informatica – University of Bari) and Giovanni Semeraro (Dipartimento di Informatica – University of Bari)
Live Session
Reproducibility of Multi-Objective Reinforcement Learning Recommendation: Interplay between Effectiveness and Beyond-Accuracy Perspectives
Vincenzo Paparella (Politecnico di Bari), Vito Walter Anelli (Politecnico di Bari), Ludovico Boratto (University of Cagliari) and Tommaso Di Noia (Politecnico di Bari)
Live Session
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 and Sunghun Kim
Live Session
Retrieval-augmented Recommender System: Enhancing Recommender Systems with Large Language Models
Dario Di Palma (Politecnico di Bari).
Live Session
Reward innovation for long term member satisfaction
Gary Tang (Netflix), Jiangwei Pan (Netflix), Henry Wang (Netflix) and Justin Basilico (Netflix)
Live Session
SPARE: Shortest Path Global Item Relations for Efficient Session-based Recommendation
Andreas Peintner (Universität Innsbruck), Amir Reza Mohammadi (Universität Innsbruck) and Eva Zangerle (Universität Innsbruck)
Live Session
STAN: Stage-Adaptive Network for Multi-Task Recommendation by Learning User Lifecycle-Based Representation
Wanda Li (Tsinghua University), Wenhao Zheng (Shopee Company), Xuanji Xiao (Shopee Company) and Suhang Wang (Penn State University)
Live Session
STRec: Sparse Transformer for Sequential Recommendations
Chengxi Li (City University of Hong Kong), Xiangyu Zhao (City University of Hong Kong), Yejing Wang (City University of Hong Kong), Qidong Liu (Xi’an Jiaotong University, City University of Hong Kong), Wanyu Wang (City University of Hong Kong), Yiqi Wang (Michigan State University), Lixin Zou (Wuhan University), Wenqi Fan (The Hong Kong Polytechnic University) and Qing Li (The Hong Kong Polytechnic University)
Live Session
Scalable Approximate NonSymmetric Autoencoder for Collaborative Filtering
Martin Spišák (GLAMI.cz and Faculty of Mathematics and Physics, Charles University, Prague, Czechia), Radek Bartyzal (GLAMI.cz), Antonín Hoskovec (GLAMI.cz and Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Czechia), Ladislav Peška (Faculty of Mathematics and Physics, Charles University, Prague, Czechia) and Miroslav Tůma (Faculty of Mathematics and Physics, Charles University, Prague, Czechia)
Live Session
Scalable Deep Q-Learning for Session-Based Slate Recommendation
Aayush Singha Roy (Insight Centre for Data Analytics, University College Dublin), Edoardo D’Amico (Insight Centre for Data Analytics, University College Dublin), Elias Tragos (Insight Centre for Data Analytics, University College Dublin), Aonghus Lawlor (Insight Centre for Data Analytics, University College Dublin) and Neil Hurley (Insight Centre for Data Analytics, University College Dublin).
Live Session
Scaling Session-Based Transformer Recommendations using Optimized Negative Sampling and Loss Functions
Timo Wilm (OTTO (GmbH & Co KG)), Philipp Normann (OTTO (GmbH & Co KG)), Sophie Baumeister (OTTO (GmbH & Co KG)) and Paul-Vincent Kobow (OTTO (GmbH & Co KG))
Live Session
Sequential Recommendation Models: A Graph-based Perspective
Andreas Peintner (University of Innsbruck)
Live Session
Stability of Explainable Recommendation
Sairamvinay Vijayaraghavan (Department of Computer Science, University of California, Davis) and Prasant Mohapatra (Department of Computer Science, University of California, Davis).
Live Session
Station and Track Attribute-Aware Music Personalization
M. Jeffrey Mei (SiriusXM Radio Inc.), Oliver Bembom (SiriusXM Radio Inc.) and Andreas Ehmann (SiriusXM Radio Inc.).
Live Session
Task Aware Feature Extraction Framework for Sequential Dependence Multi-Task Learning
Xuewen Tao (Mybank, Ant Group), Mingming Ha (School of Automation and Electrical Engineering, University of Science and Technology Bejing; Mybank, Ant Group), Qiongxu Ma (Mybank, Ant Group), Hongwei Cheng (Mybank, Ant Group), Wenfang Lin (Mybank, Ant Group) and Xiaobo Guo (Institute of Information Science, Beijing Jiaotong Univeristy; Mybank, Ant Group)
Live Session
The effect of third party implementations on reproducibility
Balázs Hidasi (Gravity R&D, a Taboola company) and Ádám Tibor Czapp (Gravity R&D, a Taboola company)
Live Session
Ti-DC-GNN: Incorporating Time-Interval Dual Graphs for Recommender Systems
Nikita Severin (HSE University), Andrey Savchenko (Sber AI Lab), Dmitrii Kiselev (Artificial Intelligence Research Institute (AIRI)), Maria Ivanova (Sber AI Lab), Ivan Kireev (Sber AI Lab) and Ilya Makarov (Artificial Intelligence Research Institute (AIRI)).
Live Session
Time-Aware Item Weighting for the Next Basket Recommendations
Aleksey Romanov (National Research University Higher School of Economics), Oleg Lashinin (Tinkoff), Marina Ananyeva (National Research University Higher School of Economics) and Sergey Kolesnikov (Tinkoff.AI).
Live Session
Topic-Level Bayesian Surprise and Serendipity for Recommender Systems
Tonmoy Hasan (UNC Charlotte) and Razvan Bunescu (UNC Charlotte).
Live Session
Towards Companion Recommenders Assisting Users' Long-Term Journeys
Konstantina Christakopoulou (Google) and Minmin Chen (Google).
Live Session
Towards Health-Aware Fairness in Food Recipe Recommendation
Mehrdad Rostami (University of Oulu), Mohammad Aliannejadi (University of Amsterdam) and Mourad Oussalah (University of Oulu).
Live Session
Towards Robust Fairness-aware Recommendation
Hao Yang (Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China), Zhining Liu (Ant Group), Zeyu Zhang (Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China), Chenyi Zhuang (Ant Group) and Xu Chen (Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China)
Live Session
Towards Self-Explaining Sequence-Aware Recommendation
Alejandro Ariza-Casabona (University of Barcelona), Maria Salamo (Universitat de Barcelona), Ludovico Boratto (University of Cagliari) and Gianni Fenu (University of Cagliari).
Live Session
Towards Sustainability-aware Recommender Systems: Analyzing the Trade-off Between Algorithms Performance and Carbon Footprint
Giuseppe Spillo (University of Bari), Allegra De Filippo (University of Bologna), Cataldo Musto (Dipartimento di Informatica – University of Bari), Michela Milano (University of Bologna) and Giovanni Semeraro (University of Bari).
Live Session
Towards the Understanding and Modeling of Passive-Negative Feedback in Sequential Short-video Recommendation
Yunzhu Pan (UESTC), Chen Gao (Tsinghua University), Yang Song (Kuaishou Inc.), Kun Gai (Unaffiliated), Depeng Jin (Department of Electronic Engineering, Tsinghua University) and Yong Li (Tsinghua University)
Live Session
Track Mix Generation on Music Streaming Services using Transformers
Walid Bendada (Deezer Research), Théo Bontempelli (Deezer Research), Mathieu Morlon (Deezer Research), Benjamin Chapus (Deezer Research), Thibault Cador (Deezer Research), Thomas Bouabça (Deezer Research) and Guillaume Salha-Galvan (Deezer Research)
Live Session
Transparently Serving the Public: Enhancing Public Service Media Values through Exploration
Andreas Grün (ZDF) and Xenija Neufeld (Accso – Accelerated Solutions GmbH).
Live Session
Trending Now: Modeling Trend Recommendations
Hao Ding, Branislav Kveton, Yifei Ma, Youngsuk Park, Venkataramana Kini, Yupeng Gu, Ravi Divvela, Fei Wang, Anoop Deoras and Hao Wang
Live Session
Turning Dross Into Gold Loss: is BERT4Rec really better than SASRec?
Anton Klenitskiy (Sber, AI Lab) and Alexey Vasilev (Sber, AI Lab).
Live Session
Two-sided Calibration for Quality-aware Responsible Recommendation
Chenyang Wang (Tsinghua University), Yankai Liu (China Mobile Research), Yuanqing Yu (Tsinghua University), Weizhi Ma (Tsinghua University), Min Zhang (Tsinghua University), Yiqun Liu (Tsinghua University), Haitao Zeng (China Mobile Research), Junlan Feng (China Mobile Research) and Chao Deng (China Mobile Research)
Live Session
Uncertainty-adjusted Inductive Matrix Completion with Graph Neural Networks
Petr Kasalicky (Singapore Management University, School of Computing and Information Systems), Antoine Ledent (Singapore Management University, School of Computing and Information Systems) and Rodrigo Alves (Czech Technical University, Faculty of Information Technology).
Live Session
Uncovering ChatGPT's Capabilities in Recommender Systems
Sunhao Dai (Renmin University of China), Ninglu Shao (Renmin University of China), Haiyuan Zhao (Renmin University of China), Weijie Yu (University of International Business and Economics), Zihua Si (Renmin University of China), Chen Xu (Renmin University of China), Zhongxiang Sun (Renmin University of China), Xiao Zhang (Renmin University of China) and Jun Xu (Renmin University of China).
Live Session
Uncovering User Interest from Biased and Noised Watch Time in Video Recommendation
Haiyuan Zhao (Renmin University of China), Lei Zhang (Renmin University of China), Jun Xu (Renmin University of China), Guohao Cai (Huawei Noah’s ark lab), Zhenhua Dong (Huawei Noah’s ark lab) and Ji-Rong Wen (Renmin University of China)
Live Session
Unleash the Power of Context: Enhancing Large-Scale Recommender Systems with Context-Based Prediction Models
Jan Hartman (Outbrain), Assaf Klein (Outbrain), Davorin Kopič (Outbrain) and Natalia Silberstein (Outbrain)
Live Session
User-Centric Conversational Recommendation: Adapting the Need of User with Language Models
Gangyi Zhang (University of Science and Technology of China).
Live Session
Using Learnable Physics for Real-Time Exercise Form Recommendations
Abhishek Jaiswal (Indian Institute of Technology Kanpur), Gautam Chauhan (Indian Institute of Technology Kanpur) and Nisheeth Srivastava (Indian Institute of Technology Kanpur)
Live Session
Visual Representation for Capturing Creator Theme in Brands-Creators Marketplace
Asnat Greenstein-Messica (Lightricks), Keren Gaiger (Lightricks), Sarel Duanis (Lightricks), Ravid Cohen (Lightricks) and Shaked Zychlinski (Lightricks)
Live Session
We’re in This Together: A Multi-Stakeholder Approach for News Recommenders
Annelien Smets, Jonathan Hendrickx and Pieter Ballon
Live Session
What We Evaluate When We Evaluate Recommender Systems: Understanding Recommender Systems’ Performance using Item Response Theory
Yang Liu (University of Helsinki), Alan Medlar (University of Helsinki) and Dorota Glowacka (University of Helsinki)
Live Session
When Fairness meets Bias: a Debiased Framework for Fairness aware Top-N Recommendation
Jiakai Tang (Gaoling School of Artificial Intelligence, Renmin University of China), Shiqi Shen (Wechat, Tencent, Beijing), Zhipeng Wang (Wechat, Tencent, Beijing), Zhi Gong (Wechat, Tencent, Beijing), Jingsen Zhang (Gaoling School of Artificial Intelligence, Renmin University of China) and Xu Chen (Gaoling School of Artificial Intelligence, Renmin University of China)
Live Session
Widespread flaws in offline evaluation of recommender systems
Balázs Hidasi (Gravity R&D, a Taboola company) and Ádám Tibor Czapp (Gravity R&D, a Taboola company).
Live Session
acourec-an-acoustic-attenuation-inspired-approach-for-effective-sequential-behavior-modeling-in-multi-task-recommender-systems
Jiawei Zhang
Live Session
gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling
Live Session
How to Access Recordings
Recordings for tutorials and paper sessions will be available here in the library starting 24 to 48 hours after the end of the session and will be available until December 15, 2023.
Tutorial on Large Language Models for Recommendation
View on ACM LibraryWenyue Hua (Rutgers University), Lei Li (Hong Kong Baptist University), Shuyuan Xu (Rutgers University), Li Chen (Hong Kong Baptist University), Yongfeng Zhang (Rutgers University)
Live Session
Tutorial: Customer Lifetime Value Prediction: Towards the Paradigm Shift of Recommender System Objectives
View on ACM LibraryCHUHAN WU (Noah's Ark Lab, Huawei), QINGLIN JIA (Noah's Ark Lab, Huawei), ZHENHUA DONG (Noah's Ark Lab, Huawei), RUIMING TANG (Noah's Ark Lab, Huawei)
Live Session
Tutorial: On Challenges of Evaluating Recommender Systems in Offline Setting
View on ACM LibraryAixin Sun
Live Session
Tutorial: Recommenders in the Wild / Practical Evaluation Methods
View on ACM LibraryKim Falk (Binary Vikings), Morten Arngren (WundermanThompson)
Live Session
Tutorial: Trustworthy Recommender Systems: Technical, Ethical, Legal, and Regulatory Perspectives
View on ACM LibraryMARKUS SCHEDL (Johannes Kepler University Linz and Linz Institute of Technology, Austria), VITO WALTER ANELLI (Politecnico di Bari, Italy), ELISABETH LEX (Graz University of Technology, Austria)
Live Session
Tutorial: User Behavior Modeling with Deep Learning for Recommendation: Recent Advances
View on ACM LibraryWeiwen Liu (Huawei Noah's Ark Lab, China), Wei Guo (Huawei Noah's Ark Lab, Singapore), Yong Liu (Huawei Noah's Ark Lab, Singapore), Ruiming Tang (Huawei Noah's Ark Lab, China), Hao Wang (University of Science and Technology of China, China)
Live Session
How to Access Recordings
Recordings for workshops, if available, need to be requested from the individual workshop organizers. You can find their contact information on the workshop website. Please note, not all workshops were recorded.
BehavRec: Workshop on Recommendations for Behavior Change
Amon Rapp (University of Torino), Federica Cena (University of Torino), Christoph Trattner (University of Bergen), Rita Orji (Dalhousie University), Julita Vassileva (University of Saskatchewan), Alain Starke (University of Amsterdam)
Live Session
CARS: Workshop on Context-Aware Recommender Systems
Gediminas Adomavicius (University of Minnesota), Konstantin Bauman (Temple University), Bamshad Mobasher (DePaul University), Alexander Tuzhilin (NYU Stern School of Business), Moshe Unger (Tel-Aviv University)
Live Session
CONSEQUENCES: The 2nd Workshop on Causality, Counterfactuals and Sequential Decision-Making for Recommender systems
Olivier Jeunen (ShareChat), Thorsten Joachims (Cornell University), Yuta Saito (Cornell University), Harrie Oosterhuis (Radboud University), Flavian Vasile (Criteo), Yixin Wang (University of Michigan)
Live Session
DLP: International Workshop on Deep Learning Practice for High-Dimensional Sparse Data
Ruiming Tang (Huawei Noah’s Ark), Xiaoqiang Zhu (Mobvista Group), Junfeng Ge (Alibaba), Kuang-chih Lee (AliExpress), Biye Jiang (Alibaba), Xingxing Wang (Meituan), Han Zhu (Alibaba), Tao Zhuang (Alibaba), Weiwen Liu (Huawei Noah’s Ark Lab), Kan Ren (Microsoft Research), Weinan Zhang (Shanghai Jiao Tong University), Xiangyu Zhao (City University of Hong Kong)
Live Session
FAccTRec: The 6th Workshop on Responsible Recommendation
Michael D. Ekstrand (Boise State University), Jean Garcia-Gathright (Pinterest), Nasim Sonboli (Brown University), Amifa Raj (Boise State University), Karlijn Dinnissen (Utrecht University)
Live Session
INRA: International Workshop on News Recommendation and Analytic
Özlem Özgöbek (NTNU), Andreas Lommatzsch (DAI Lab, TU Berlin), Benjamin Kille (NorwAI, NTNU), Peng Liu (NorwAI, NTNU), Edward C. Malthouse, (Northwestern University), Jon Atle Gulla (NorwAI, NTNU)
Live Session
IntRS’23: 10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems
Peter Brusilovsky (School of Information Sciences, University of Pittsburgh), Marco de Gemmis (University of Bari “Aldo Moro”), Alexander Felfernig (Institute for Software Technology, Graz University of Technology), Pasquale Lops (University of Bari “Aldo Moro”), Marco Polignano (University of Bari “Aldo Moro”), Giovanni Semeraro (University of Bari “Aldo Moro”), Martijn C. Willemsen (Eindhoven University of Technology)
Live Session
KaRS: Fifth Knowledge-aware and Conversational Recommender Systems Workshop
Vito Walter Anelli (Polytechnic University of Bari), Pierpaolo Basile (University of Bari Aldo Moro), Gerard De Melo (Hasso Plattner Institute and University of Potsdam), Francesco Maria Donini (University of Tuscia), Antonio Ferrara (Polytechnic University of Bari), Cataldo Musto (University of Bari Aldo Moro), Fedelucio Narducci (Polytechnic University of Bari), Azzurra Ragone (University of Bari Aldo Moro), Markus Zanker (Free University of Bozen-Bolzano)
Live Session
LERI: Workshop on Learning and Evaluating Recommendations with Impressions
Justin Basilico (Netflix), Pablo Castells (Universidad Autónoma de Madrid and Amazon), Paolo Cremonesi (Politecnico di Milano), Maurizio Ferrari Dacrema (Politecnico di Milano)
Live Session
MuRS: Music Recommender Systems Workshop
Andrés Ferraro (Pandora-SiriusXM), Peter Knees (TU Wien), Massimo Quadrana, Tao Ye (Amazon), Fabien Gouyon (Pandora-SiriusXM)
Live Session
NORMalize: The 1st Workshop on Normative Design and Evaluation of Recommender Systems
Sanne Vrijenhoek (Institute of Information Law, University of Amsterdam), Lien Michiels (University of Antwerp), Johannes Kruse (Technical University of Denmark), Alain Starke (University of Amsterdam), Nava Tintarev (Maastricht University)
Live Session
ORSUM: 6th Workshop on Online Recommender Systems and User Modeling
João Vinagre (Joint Research Centre – European Commission and University of Porto), Marie Al-Ghossein (Crossing Minds), Ladislav Peška (Charles University Prague), Alípio Jorge (University of Porto), Albert Bifet (LTCI, Télécom ParisTech)
Live Session
PERSPECTIVES: 3rd Workshop: Perspectives on the Evaluation of Recommender Systems
Alan Said (University of Gothenburg), Eva Zangerle (Universität Innsbruck), Christine Bauer (Utrecht University, The Netherlands)
Live Session
QUARE: 2nd Workshop on Measuring the Quality of Explanations in Recommender Systems
Oana Inel (University of Zurich), Nicolas Mattis (Vrije Universiteit Amsterdam), Milda Norkute (Thomson Reuters Labs), Alessandro Piscopo (BBC), Timothée Schmude (University of Vienna), Sanne Vrijenhoek (Institute of Information Law, University of Amsterdam), Krisztian Balog (Google and University of Stavanger)
Live Session
RecSys Challenge
Rahul Agarwal (ShareChat), Sarang Brahme (ShareChat), Abhishek Srivastava (IIM Visakhapatnam), Liu Yong (Huawei), Athirai Irissappane (Amazon)
Live Session
RecSys in HR: 3rd Workshop on Recommender Systems for Human Resources
Toine Bogers (IT University of Copenhagen), David Graus (Randstad Groep Nederland), Mesut Kaya (Aalborg University Copenhagen), Chris Johnson (Indeed.com), Jens-Joris Decorte (TechWolf)
Live Session
RecTour: Workshop on Recommenders in Tourism 2023
Julia Neidhardt (TU Wien), Wolfgang Wörndl (Technical University of Munich), Tsvi Kuflik (The University of Haifa), Dmitri Goldenberg (Booking.com), Markus Zanker (Free University of Bozen-Bolzano and University of Klagenfurt)
Live Session
VideoRecSys: First Workshop on Large-Scale Video Recommender Systems
Khushhall Chandra Mahajan (Meta), Amey Porobo Dharwadker (Facebook), Saurabh Gupta (Meta), Brad Schumitsch (Facebook)
Live Session
fashionXrecsys: Recommender Systems in Fashion & Retail
Julia Lasserre (Zalando SE), Nima Dokoohaki (Accenture AI), Reza Shirvany (Zalando)