| 2024 | "Maya"- A Conversational Shopping Assistant for Fashion at Myntra. Akhil Raj, Hrishikesh Ganu, Saikat Kumar Das, R. Sandeep, Satyajeet Singh, Sreekanth Vempati |
| 2024 | A Linguistic Grounding-Infused Contrastive Learning Approach for Health Mention Classification on Social Media. Usman Naseem, Jinman Kim, Matloob Khushi, Adam G. Dunn |
| 2024 | A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval. Xiaojie Sun, Keping Bi, Jiafeng Guo, Sihui Yang, Qishen Zhang, Zhongyi Liu, Guannan Zhang, Xueqi Cheng |
| 2024 | A Scalable Open-Source System for Segmenting Urban Areas with Road Networks. Ming Zhang, Yanyan Li, Jianguo Duan, Jizhou Huang, Jingbo Zhou |
| 2024 | AAGenRec: A Novel Approach for Mitigating Inter-task Interference in Multi-task Optimization of Sequential Behavior Modeling. Jiawei Zhang, Shimin Yang, Liang Shen |
| 2024 | Accelerating Pharmacovigilance using Large Language Models. Mukkamala Venkata Sai Prakash, Ganesh Parab, Meghana Veeramalla, Siddartha Reddy, Varun V, Saisubramaniam Gopalakrishnan, Vishal Pagidipally, Vishal Vaddina |
| 2024 | Ad-load Balancing via Off-policy Learning in a Content Marketplace. Hitesh Sagtani, Madan Gopal Jhawar, Rishabh Mehrotra, Olivier Jeunen |
| 2024 | An Interpretable Brain Graph Contrastive Learning Framework for Brain Disorder Analysis. Xuexiong Luo, Guangwei Dong, Jia Wu, Amin Beheshti, Jian Yang, Shan Xue |
| 2024 | Applications of LLMs in E-Commerce Search and Product Knowledge Graph: The DoorDash Case Study. Sudeep Das, Raghav Saboo, Chaitanya S. K. Vadrevu, Bruce Wang, Steven Xu |
| 2024 | Attribute Simulation for Item Embedding Enhancement in Multi-interest Recommendation. Yaokun Liu, Xiaowang Zhang, Minghui Zou, Zhiyong Feng |
| 2024 | Augmenting Keyword-based Search in Mobile Applications Using LLMs. Harikrishnan C, Giridhar Sreenivasa Murthy, Kumar Rangarajan |
| 2024 | AutoPooling: Automated Pooling Search for Multi-valued Features in Recommendations. He Wei, Yuekui Yang, Shaoping Ma, Haiyang Wu, Yangyang Tang, Meixi Liu, Yang Zhang |
| 2024 | Automated Tailoring of Large Language Models for Industry-Specific Downstream Tasks. Shreya Saxena, Siva Prasad, Muneeswaran I, Advaith Shankar, Varun V, Saisubramaniam Gopalakrishnan, Vishal Vaddina |
| 2024 | Automated Topic Generation for the Mexican Platform for Access to Government Public Information During the Period 2003-2020. Hermelando Cruz-Pérez, Alejandro Molina-Villegas |
| 2024 | Automatic Extraction of Patterns in Digital News Articles of Femicides occurred in Mexico by Text Mining Techniques. Jonathan Zárate-Cartas, Alejandro Molina-Villegas |
| 2024 | Bridging Text Data and Graph Data: Towards Semantics and Structure-aware Knowledge Discovery. Bowen Jin, Yu Zhang, Sha Li, Jiawei Han |
| 2024 | Budgeted Embedding Table For Recommender Systems. Yunke Qu, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin |
| 2024 | CDRNP: Cross-Domain Recommendation to Cold-Start Users via Neural Process. Xiaodong Li, Jiawei Sheng, Jiangxia Cao, Wenyuan Zhang, Quangang Li, Tingwen Liu |
| 2024 | CL4DIV: A Contrastive Learning Framework for Search Result Diversification. Zhirui Deng, Zhicheng Dou, Yutao Zhu, Ji-Rong Wen |
| 2024 | COTER: Conditional Optimal Transport meets Table Retrieval. Xun Yao, Zhixin Zhang, Xinrong Hu, Jie (Jack) Yang, Yi Guo, Daniel (Dianliang) Zhu |
| 2024 | Calibration-compatible Listwise Distillation of Privileged Features for CTR Prediction. Xiaoqiang Gui, Yueyao Cheng, Xiang-Rong Sheng, Yunfeng Zhao, Guoxian Yu, Shuguang Han, Yuning Jiang, Jian Xu, Bo Zheng |
| 2024 | Capturing Temporal Node Evolution via Self-supervised Learning: A New Perspective on Dynamic Graph Learning. Lingwen Liu, Guangqi Wen, Peng Cao, Jinzhu Yang, Weiping Li, Osmar R. Zaïane |
| 2024 | CausalMMM: Learning Causal Structure for Marketing Mix Modeling. Chang Gong, Di Yao, Lei Zhang, Sheng Chen, Wenbin Li, Yueyang Su, Jingping Bi |
| 2024 | Causality Guided Disentanglement for Cross-Platform Hate Speech Detection. Paras Sheth, Raha Moraffah, Tharindu S. Kumarage, Aman Chadha, Huan Liu |
| 2024 | CharmBana: Progressive Responses with Real-Time Internet Search for Knowledge-Powered Conversations. Revanth Gangi Reddy, Sharath Chandra Etagi Suresh, Hao Bai, Wentao Yao, Mankeerat Sidhu, Karan Aggarwal, Prathamesh Sonawane, ChengXiang Zhai |
| 2024 | CityCAN: Causal Attention Network for Citywide Spatio-Temporal Forecasting. Chengxin Wang, Yuxuan Liang, Gary Tan |
| 2024 | Collaboration and Transition: Distilling Item Transitions into Multi-Query Self-Attention for Sequential Recommendation. Tianyu Zhu, Yansong Shi, Yuan Zhang, Yihong Wu, Fengran Mo, Jian-Yun Nie |
| 2024 | Contextual MAB Oriented Embedding Denoising for Sequential Recommendation. Zhichao Feng, Pengfei Wang, Kaiyuan Li, Chenliang Li, Shangguang Wang |
| 2024 | Continuous-time Autoencoders for Regular and Irregular Time Series Imputation. Hyowon Wi, Yehjin Shin, Noseong Park |
| 2024 | Cost-Effective Active Learning for Bid Exploration in Online Advertising. Zixiao Wang, Zhenzhe Zheng, Yanrong Kang, Jiani Huang |
| 2024 | CreST: A Credible Spatiotemporal Learning Framework for Uncertainty-aware Traffic Forecasting. Zhengyang Zhou, Jiahao Shi, Hongbo Zhang, Qiongyu Chen, Xu Wang, Hongyang Chen, Yang Wang |
| 2024 | CroSSL: Cross-modal Self-Supervised Learning for Time-series through Latent Masking. Shohreh Deldari, Dimitris Spathis, Mohammad Malekzadeh, Fahim Kawsar, Flora D. Salim, Akhil Mathur |
| 2024 | Customer Understanding for Recommender Systems. Md. Mostafizur Rahman, Yu Hirate |
| 2024 | Customized and Robust Deep Neural Network Watermarking. Tzu-Yun Chien, Chih-Ya Shen |
| 2024 | C²DR: Robust Cross-Domain Recommendation based on Causal Disentanglement. Menglin Kong, Jia Wang, Yushan Pan, Haiyang Zhang, Muzhou Hou |
| 2024 | Dance with Labels: Dual-Heterogeneous Label Graph Interaction for Multi-intent Spoken Language Understanding. Zhihong Zhu, Xuxin Cheng, Hongxiang Li, Yaowei Li, Yuexian Zou |
| 2024 | DeSCo: Towards Generalizable and Scalable Deep Subgraph Counting. Tianyu Fu, Chiyue Wei, Yu Wang, Rex Ying |
| 2024 | Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure. Jiyuan Yang, Yue Ding, Yidan Wang, Pengjie Ren, Zhumin Chen, Fei Cai, Jun Ma, Rui Zhang, Zhaochun Ren, Xin Xin |
| 2024 | Deep Evolutional Instant Interest Network for CTR Prediction in Trigger-Induced Recommendation. Zhibo Xiao, Luwei Yang, Tao Zhang, Wen Jiang, Wei Ning, Yujiu Yang |
| 2024 | Defense Against Model Extraction Attacks on Recommender Systems. Sixiao Zhang, Hongzhi Yin, Hongxu Chen, Cheng Long |
| 2024 | Delphic Costs and Benefits in Web Search: A Utilitarian and Historical Analysis. Andrei Z. Broder |
| 2024 | Diff-MSR: A Diffusion Model Enhanced Paradigm for Cold-Start Multi-Scenario Recommendation. Yuhao Wang, Ziru Liu, Yichao Wang, Xiangyu Zhao, Bo Chen, Huifeng Guo, Ruiming Tang |
| 2024 | DiffKG: Knowledge Graph Diffusion Model for Recommendation. Yangqin Jiang, Yuhao Yang, Lianghao Xia, Chao Huang |
| 2024 | Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. Fali Wang, Tianxiang Zhao, Suhang Wang |
| 2024 | Domain Level Interpretability: Interpreting Black-box Model with Domain-specific Embedding. Ya-Lin Zhang, Caizhi Tang, Lu Yu, Jun Zhou, Longfei Li, Qing Cui, Fangfang Fan, Linbo Jiang, Xiaosong Zhao |
| 2024 | Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation. Shuyao Wang, Yongduo Sui, Jiancan Wu, Zhi Zheng, Hui Xiong |
| 2024 | Effective and Efficient Transformer Models for Sequential Recommendation. Aleksandr V. Petrov |
| 2024 | Efficient, Direct, and Restricted Black-Box Graph Evasion Attacks to Any-Layer Graph Neural Networks via Influence Function. Binghui Wang, Minhua Lin, Tianxiang Zhou, Pan Zhou, Ang Li, Meng Pang, Hai Helen Li, Yiran Chen |
| 2024 | Empathetic Response Generation with Relation-aware Commonsense Knowledge. Changyu Chen, Yanran Li, Chen Wei, Jianwei Cui, Bin Wang, Rui Yan |
| 2024 | EvidenceQuest: An Interactive Evidence Discovery System for Explainable Artificial Intelligence. Ambreen Hanif, Amin Beheshti, Xuyun Zhang, Steven Wood, Boualem Benatallah, EuJin Foo |
| 2024 | Exploiting Duality in Open Information Extraction with Predicate Prompt. Zhen Chen, Jingping Liu, Deqing Yang, Yanghua Xiao, Huimin Xu, Zongyu Wang, Rui Xie, Yunsen Xian |
| 2024 | Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights. Junchen Fu, Fajie Yuan, Yu Song, Zheng Yuan, Mingyue Cheng, Shenghui Cheng, Jiaqi Zhang, Jie Wang, Yunzhu Pan |
| 2024 | FairIF: Boosting Fairness in Deep Learning via Influence Functions with Validation Set Sensitive Attributes. Haonan Wang, Ziwei Wu, Jingrui He |
| 2024 | Fly-Swat or Cannon? Cost-Effective Language Model Choice via Meta-Modeling. Marija Sakota, Maxime Peyrard, Robert West |
| 2024 | Follow the LIBRA: Guiding Fair Policy for Unified Impression Allocation via Adversarial Rewarding. Xiaoyu Wang, Yonghui Guo, Bin Tan, Tao Yang, Dongbo Huang, Lan Xu, Hao Zhou, Xiangyang Li |
| 2024 | Foundation Models for Aerial Robotics. Ashish Kapoor |
| 2024 | Framework for Bias Detection in Machine Learning Models: A Fairness Approach. Alveiro Alonso Rosado Gomez, Maritza Liliana Calderón-Benavides |
| 2024 | Fresh Content Recommendation at Scale: A Multi-funnel Solution and the Potential of LLMs. Jianling Wang, Haokai Lu, Minmin Chen |
| 2024 | From Second to First: Mixed Censored Multi-Task Learning for Winning Price Prediction. Jiani Huang, Zhenzhe Zheng, Yanrong Kang, Zixiao Wang |
| 2024 | Future Timelines: Extraction and Visualization of Future-related Content From News Articles. Juwal Regev, Adam Jatowt, Michael Färber |
| 2024 | GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction. Amit Roy, Juan Shu, Jia Li, Carl Yang, Olivier Elshocht, Jeroen Smeets, Pan Li |
| 2024 | GAP: A Grammar and Position-Aware Framework for Efficient Recognition of Multi-Line Mathematical Formulas. Zhe Yang, Qi Liu, Kai Zhang, Shiwei Tong, Enhong Chen |
| 2024 | GEMRec: Towards Generative Model Recommendation. Yuanhe Guo, Haoming Liu, Hongyi Wen |
| 2024 | Gaussian Graphical Model-Based Clustering of Time Series Data. Kohei Obata |
| 2024 | Generative Models for Complex Logical Reasoning over Knowledge Graphs. Yu Liu, Yanan Cao, Shi Wang, Qingyue Wang, Guanqun Bi |
| 2024 | Genomic-World Fungi Data: Synteny Part. Pedro Escobar-Turriza, Luis Muñoz-Miranda, Alejandro Pereira-Santana |
| 2024 | Ginkgo-P: General Illustrations of Knowledge Graphs for Openness as a Platform. Blaine Hill, Lihui Liu, Hanghang Tong |
| 2024 | Global Heterogeneous Graph and Target Interest Denoising for Multi-behavior Sequential Recommendation. Xuewei Li, Hongwei Chen, Jian Yu, Mankun Zhao, Tianyi Xu, Wenbin Zhang, Mei Yu |
| 2024 | Grounded and Transparent Response Generation for Conversational Information-Seeking Systems. Weronika Lajewska |
| 2024 | Guardian: Guarding against Gradient Leakage with Provable Defense for Federated Learning. Mingyuan Fan, Yang Liu, Cen Chen, Chengyu Wang, Minghui Qiu, Wenmeng Zhou |
| 2024 | HealAI: A Healthcare LLM for Effective Medical Documentation. Sagar Goyal, Eti Rastogi, Sree Prasanna Rajagopal, Dong Yuan, Fen Zhao, Jai Chintagunta, Gautam Naik, Jeff Ward |
| 2024 | Hierarchical Multimodal Pre-training for Visually Rich Webpage Understanding. Hongshen Xu, Lu Chen, Zihan Zhao, Da Ma, Ruisheng Cao, Zichen Zhu, Kai Yu |
| 2024 | IAI MovieBot 2.0: An Enhanced Research Platform with Trainable Neural Components and Transparent User Modeling. Nolwenn Bernard, Ivica Kostric, Krisztian Balog |
| 2024 | IDoFew: Intermediate Training Using Dual-Clustering in Language Models for Few Labels Text Classification. Abdullah Alsuhaibani, Hamad Zogan, Imran Razzak, Shoaib Jameel, Guandong Xu |
| 2024 | IncMSR: An Incremental Learning Approach for Multi-Scenario Recommendation. Kexin Zhang, Yichao Wang, Xiu Li, Ruiming Tang, Rui Zhang |
| 2024 | Incomplete Graph Learning via Attribute-Structure Decoupled Variational Auto-Encoder. Xinke Jiang, Zidi Qin, Jiarong Xu, Xiang Ao |
| 2024 | Integrating Knowledge Graph Data with Large Language Models for Explainable Inference. Carlos Efrain Quintero Narvaez, Raúl Monroy |
| 2024 | Integrity 2024: Integrity in Social Networks and Media. Lluís Garcia Pueyo, Symeon Papadopoulos, Prathyusha Senthil Kumar, Aristides Gionis, Panayiotis Tsaparas, Vasilis Verroios, Giuseppe Manco, Anton Andryeyev, Stefano Cresci, Timos Sellis, Anthony McCosker |
| 2024 | Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation. Xiuyuan Qin, Huanhuan Yuan, Pengpeng Zhao, Guanfeng Liu, Fuzhen Zhuang, Victor S. Sheng |
| 2024 | Interact with the Explanations: Causal Debiased Explainable Recommendation System. Xu Liu, Tong Yu, Kaige Xie, Junda Wu, Shuai Li |
| 2024 | Interpretable Imitation Learning with Dynamic Causal Relations. Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen |
| 2024 | Introduction to Responsible AI. Ricardo Baeza-Yates |
| 2024 | Inverse Learning with Extremely Sparse Feedback for Recommendation. Guanyu Lin, Chen Gao, Yu Zheng, Yinfeng Li, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li |
| 2024 | Journey of Hallucination-minimized Generative AI Solutions for Financial Decision Makers. Sohini Roychowdhury |
| 2024 | K2: A Foundation Language Model for Geoscience Knowledge Understanding and Utilization. Cheng Deng, Tianhang Zhang, Zhongmou He, Qiyuan Chen, Yuanyuan Shi, Yi Xu, Luoyi Fu, Weinan Zhang, Xinbing Wang, Chenghu Zhou, Zhouhan Lin, Junxian He |
| 2024 | Knowledge Graph Context-Enhanced Diversified Recommendation. Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Mingdai Yang, Chen Wang, Hao Peng, Philip S. Yu |
| 2024 | LEAD: Liberal Feature-based Distillation for Dense Retrieval. Hao Sun, Xiao Liu, Yeyun Gong, Anlei Dong, Jingwen Lu, Yan Zhang, Linjun Yang, Rangan Majumder, Nan Duan |
| 2024 | LLMRec: Large Language Models with Graph Augmentation for Recommendation. Wei Wei, Xubin Ren, Jiabin Tang, Qinyong Wang, Lixin Su, Suqi Cheng, Junfeng Wang, Dawei Yin, Chao Huang |
| 2024 | LMBot: Distilling Graph Knowledge into Language Model for Graph-less Deployment in Twitter Bot Detection. Zijian Cai, Zhaoxuan Tan, Zhenyu Lei, Zifeng Zhu, Hongrui Wang, Qinghua Zheng, Minnan Luo |
| 2024 | LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting. Yimeng Bai, Yang Zhang, Jing Lu, Jianxin Chang, Xiaoxue Zang, Yanan Niu, Yang Song, Fuli Feng |
| 2024 | Learning Opinion Dynamics from Data. Jacopo Lenti |
| 2024 | Lessons Learnt from Building Friend Recommendation Systems. Jun Yu |
| 2024 | Let the LLMs Talk: Simulating Human-to-Human Conversational QA via Zero-Shot LLM-to-LLM Interactions. Zahra Abbasiantaeb, Yifei Yuan, Evangelos Kanoulas, Mohammad Aliannejadi |
| 2024 | Leveraging Multimodal Features and Item-level User Feedback for Bundle Construction. Yunshan Ma, Xiaohao Liu, Yinwei Wei, Zhulin Tao, Xiang Wang, Tat-Seng Chua |
| 2024 | Leveraging User Simulation to Develop and Evaluate Conversational Information Access Agents. Nolwenn Bernard |
| 2024 | Likelihood-Based Methods Improve Parameter Estimation in Opinion Dynamics Models. Jacopo Lenti, Corrado Monti, Gianmarco De Francisci Morales |
| 2024 | Linear Recurrent Units for Sequential Recommendation. Zhenrui Yue, Yueqi Wang, Zhankui He, Huimin Zeng, Julian J. McAuley, Dong Wang |
| 2024 | Logic-Scaffolding: Personalized Aspect-Instructed Recommendation Explanation Generation using LLMs. Behnam Rahdari, Hao Ding, Ziwei Fan, Yifei Ma, Zhuotong Chen, Anoop Deoras, Branislav Kveton |
| 2024 | Long-Term Value of Exploration: Measurements, Findings and Algorithms. Yi Su, Xiangyu Wang, Elaine Ya Le, Liang Liu, Yuening Li, Haokai Lu, Benjamin Lipshitz, Sriraj Badam, Lukasz Heldt, Shuchao Bi, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen |
| 2024 | MAD: Multi-Scale Anomaly Detection in Link Streams. Esteban Bautista, Laurent Brisson, Cécile Bothorel, Grégory Smits |
| 2024 | MADM: A Model-agnostic Denoising Module for Graph-based Social Recommendation. Wenze Ma, Yuexian Wang, Yanmin Zhu, Zhaobo Wang, Mengyuan Jing, Xuhao Zhao, Jiadi Yu, Feilong Tang |
| 2024 | MONET: Modality-Embracing Graph Convolutional Network and Target-Aware Attention for Multimedia Recommendation. Yungi Kim, Taeri Kim, Won-Yong Shin, Sang-Wook Kim |
| 2024 | Making Small Language Models Better Multi-task Learners with Mixture-of-Task-Adapters. Yukang Xie, Chengyu Wang, Junbing Yan, Jiyong Zhou, Feiqi Deng, Jun Huang |
| 2024 | Maximizing Malicious Influence in Node Injection Attack. Xiao Zhang, Peng Bao, Shirui Pan |
| 2024 | Mitigating Factual Inconsistency and Hallucination in Large Language Models. Muneeswaran I, Advaith Shankar, Varun V, Saisubramaniam Gopalakrishnan, Vishal Vaddina |
| 2024 | Mixed Attention Network for Cross-domain Sequential Recommendation. Guanyu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li, Meng Wang |
| 2024 | Motif-based Prompt Learning for Universal Cross-domain Recommendation. Bowen Hao, Chaoqun Yang, Lei Guo, Junliang Yu, Hongzhi Yin |
| 2024 | Multi-Granular Text Classification with Minimal Supervision. Yunyi Zhang |
| 2024 | Multi-Intent Attribute-Aware Text Matching in Searching. Mingzhe Li, Xiuying Chen, Jing Xiang, Qishen Zhang, Changsheng Ma, Chenchen Dai, Jinxiong Chang, Zhongyi Liu, Guannan Zhang |
| 2024 | Multi-Sequence Attentive User Representation Learning for Side-information Integrated Sequential Recommendation. Xiaolin Lin, Jinwei Luo, Junwei Pan, Weike Pan, Zhong Ming, Xun Liu, Shudong Huang, Jie Jiang |
| 2024 | MultiFS: Automated Multi-Scenario Feature Selection in Deep Recommender Systems. Dugang Liu, Chaohua Yang, Xing Tang, Yejing Wang, Fuyuan Lyu, Weihong Luo, Xiuqiang He, Zhong Ming, Xiangyu Zhao |
| 2024 | MultiSPANS: A Multi-range Spatial-Temporal Transformer Network for Traffic Forecast via Structural Entropy Optimization. Dongcheng Zou, Senzhang Wang, Xuefeng Li, Hao Peng, Yuandong Wang, Chunyang Liu, Kehua Sheng, Bo Zhang |
| 2024 | Neural Kalman Filtering for Robust Temporal Recommendation. Jiafeng Xia, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang, Ning Gu |
| 2024 | NeuralReconciler for Hierarchical Time Series Forecasting. Shiyu Wang |
| 2024 | Not All Negatives Are Worth Attending to: Meta-Bootstrapping Negative Sampling Framework for Link Prediction. Yakun Wang, Binbin Hu, Shuo Yang, Meiqi Zhu, Zhiqiang Zhang, Qiyang Zhang, Jun Zhou, Guo Ye, Huimei He |
| 2024 | ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models. Qijiong Liu, Nuo Chen, Tetsuya Sakai, Xiao-Ming Wu |
| 2024 | On the Effectiveness of Unlearning in Session-Based Recommendation. Xin Xin, Liu Yang, Ziqi Zhao, Pengjie Ren, Zhumin Chen, Jun Ma, Zhaochun Ren |
| 2024 | Overlapping and Robust Edge-Colored Clustering in Hypergraphs. Alex Crane, Brian Lavallee, Blair D. Sullivan, Nate Veldt |
| 2024 | PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation. Chunjing Gan, Bo Huang, Binbin Hu, Jian Ma, Zhiqiang Zhang, Jun Zhou, Guannan Zhang, Wenliang Zhong |
| 2024 | PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models. Wei-Cheng Chang, Jyun-Yu Jiang, Jiong Zhang, Mutasem Al-Darabsah, Choon Hui Teo, Cho-Jui Hsieh, Hsiang-Fu Yu, S. V. N. Vishwanathan |
| 2024 | PhoGAD: Graph-based Anomaly Behavior Detection with Persistent Homology Optimization. Ziqi Yuan, Haoyi Zhou, Tianyu Chen, Jianxin Li |
| 2024 | Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices. Jing Zhu, Yuhang Zhou, Vassilis N. Ioannidis, Shengyi Qian, Wei Ai, Xiang Song, Danai Koutra |
| 2024 | Practical Bandits: An Industry Perspective. Bram van den Akker, Olivier Jeunen, Ying Li, Ben London, Zahra Nazari, Devesh Parekh |
| 2024 | Pre-trained Recommender Systems: A Causal Debiasing Perspective. Ziqian Lin, Hao Ding, Trong Nghia Hoang, Branislav Kveton, Anoop Deoras, Hao Wang |
| 2024 | Preserving Heritage: Developing a Translation Tool for Indigenous Dialects. Melissa Robles, Cristian A. Martínez, Juan Camilo Prieto, Sara Palacios, Rubén Manrique |
| 2024 | ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees. Sina Sajadmanesh, Daniel Gatica-Perez |
| 2024 | Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024 Luz Angelica Caudillo-Mata, Silvio Lattanzi, Andrés Muñoz Medina, Leman Akoglu, Aristides Gionis, Sergei Vassilvitskii |
| 2024 | Professional Network Matters: Connections Empower Person-Job Fit. Hao Chen, Lun Du, Yuxuan Lu, Qiang Fu, Xu Chen, Shi Han, Yanbin Kang, Guangming Lu, Zi Li |
| 2024 | Profiling Urban Mobility Patterns with High Spatial and Temporal Resolution: A Deep Dive into Cellphone Geo-position Data. José Ignacio Huertas, Luisa Fernanda Chaparro Sierra |
| 2024 | Proxy-based Item Representation for Attribute and Context-aware Recommendation. Jinseok Seol, Minseok Gang, Sang-goo Lee, Jaehui Park |
| 2024 | Psychology-informed Information Access Systems Workshop. Markus Schedl, Marta Moscati, Bruno Sguerra, Romain Hennequin, Elisabeth Lex |
| 2024 | RDGCN: Reinforced Dependency Graph Convolutional Network for Aspect-based Sentiment Analysis. Xusheng Zhao, Hao Peng, Qiong Dai, Xu Bai, Huailiang Peng, Yanbing Liu, Qinglang Guo, Philip S. Yu |
| 2024 | Ranking with Long-Term Constraints. Kianté Brantley, Zhichong Fang, Sarah Dean, Thorsten Joachims |
| 2024 | Real-time E-bike Route Planning with Battery Range Prediction. Zhao Li, Guoqi Ren, Yongchun Gu, Siwei Zhou, Xuanwu Liu, Jiaming Huang, Ming Li |
| 2024 | RecJPQ: Training Large-Catalogue Sequential Recommenders. Aleksandr V. Petrov, Craig Macdonald |
| 2024 | Recent Advances in Refinement Recommendations. Akshay Jagatap, Sachin Farfade |
| 2024 | Rethinking and Simplifying Bootstrapped Graph Latents. Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng |
| 2024 | Robust Training for Conversational Question Answering Models with Reinforced Reformulation Generation. Magdalena Kaiser, Rishiraj Saha Roy, Gerhard Weikum |
| 2024 | SCAD: Subspace Clustering based Adversarial Detector. Xinrong Hu, Wushuan Chen, Jie Yang, Yi Guo, Xun Yao, Bangchao Wang, Junping Liu, Ce Xu |
| 2024 | SIRUP: Search-based Book Recommendation Playground. Ghazaleh Haratinezhad Torbati, Anna Tigunova, Gerhard Weikum |
| 2024 | SSLRec: A Self-Supervised Learning Framework for Recommendation. Xubin Ren, Lianghao Xia, Yuhao Yang, Wei Wei, Tianle Wang, Xuheng Cai, Chao Huang |
| 2024 | Scaling Up LLM Reviews for Google Ads Content Moderation. Wei Qiao, Tushar Dogra, Otilia Stretcu, Yu-Han Lyu, Tiantian Fang, Dongjin Kwon, Chun-Ta Lu, Enming Luo, Yuan Wang, Chih-Chun Chia, Ariel Fuxman, Fangzhou Wang, Ranjay Krishna, Mehmet Tek |
| 2024 | Scaling Use-case Based Shopping using LLMs. Sachin Farfade, Sachin Vernekar, Vineet Chaoji, Rajdeep Mukherjee |
| 2024 | Some Useful Things to Know When Combining IR and NLP: The Easy, the Hard and the Ugly. Omar Alonso, Kenneth Church |
| 2024 | Source Free Graph Unsupervised Domain Adaptation. Haitao Mao, Lun Du, Yujia Zheng, Qiang Fu, Zelin Li, Xu Chen, Shi Han, Dongmei Zhang |
| 2024 | Strategic ML: How to Learn With Data That 'Behaves'. Nir Rosenfeld |
| 2024 | TTC-QuAli: A Text-Table-Chart Dataset for Multimodal Quantity Alignment. Haoyu Dong, Haochen Wang, Anda Zhou, Yue Hu |
| 2024 | Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study. Yuan Sui, Mengyu Zhou, Mingjie Zhou, Shi Han, Dongmei Zhang |
| 2024 | Temporal Blind Spots in Large Language Models. Jonas Wallat, Adam Jatowt, Avishek Anand |
| 2024 | Temporal Graph Analysis with TGX. Razieh Shirzadkhani, Shenyang Huang, Elahe Kooshafar, Reihaneh Rabbany, Farimah Poursafaei |
| 2024 | TemporalMed: Advancing Medical Dialogues with Time-Aware Responses in Large Language Models. Yuyan Chen, Jin Zhao, Zhihao Wen, Zhixu Li, Yanghua Xiao |
| 2024 | Text-Video Retrieval via Multi-Modal Hypergraph Networks. Qian Li, Lixin Su, Jiashu Zhao, Long Xia, Hengyi Cai, Suqi Cheng, Hengzhu Tang, Junfeng Wang, Dawei Yin |
| 2024 | The 3rd International Workshop on Interactive and Scalable Information Retrieval Methods for eCommerce (ISIR-eCom 2024). Vachik S. Dave, Linsey Pang, Xiquan Cui, Chen Luo, Hamed Zamani, Lingfei Wu, George Karypis |
| 2024 | The 5th International Workshop on Machine Learning on Graphs (MLoG). Tyler Derr, Yao Ma, Kaize Ding, Tong Zhao, Nesreen K. Ahmed |
| 2024 | The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation. Yuchang Zhu, Jintang Li, Liang Chen, Zibin Zheng |
| 2024 | The Journey to A Knowledgeable Assistant with Retrieval-Augmented Generation (RAG). Xin Luna Dong |
| 2024 | To Copy, or not to Copy; That is a Critical Issue of the Output Softmax Layer in Neural Sequential Recommenders. Haw-Shiuan Chang, Nikhil Agarwal, Andrew McCallum |
| 2024 | Towards Alignment-Uniformity Aware Representation in Graph Contrastive Learning. Rong Yan, Peng Bao, Xiao Zhang, Zhongyi Liu, Hui Liu |
| 2024 | Towards Better Chinese Spelling Check for Search Engines: A New Dataset and Strong Baseline. Yue Wang, Zilong Zheng, Zecheng Tang, Juntao Li, Zhihui Liu, Kunlong Chen, Jinxiong Chang, Qishen Zhang, Zhongyi Liu, Min Zhang |
| 2024 | Towards Mitigating Dimensional Collapse of Representations in Collaborative Filtering. Huiyuan Chen, Vivian Lai, Hongye Jin, Zhimeng Jiang, Mahashweta Das, Xia Hu |
| 2024 | Towards Trustworthy Large Language Models. Sanmi Koyejo, Bo Li |
| 2024 | Unbiased Learning to Rank: On Recent Advances and Practical Applications. Shashank Gupta, Philipp Hager, Jin Huang, Ali Vardasbi, Harrie Oosterhuis |
| 2024 | Understanding User Behavior in Carousel Recommendation Systems for Click Modeling and Learning to Rank. Santiago de Leon-Martinez |
| 2024 | Unified Pretraining for Recommendation via Task Hypergraphs. Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu |
| 2024 | Unified Visual Preference Learning for User Intent Understanding. Yihua Wen, Si Chen, Yu Tian, Wanxian Guan, Pengjie Wang, Hongbo Deng, Jian Xu, Bo Zheng, Zihao Li, Lixin Zou, Chenliang Li |
| 2024 | Unlocking Human Curiosity. Elizabeth Reid |
| 2024 | Unveiling AI-Driven Collective Action for a Worker-Centric Future. Saiph Savage |
| 2024 | User Behavior Enriched Temporal Knowledge Graphs for Sequential Recommendation. Hengchang Hu, Wei Guo, Xu Liu, Yong Liu, Ruiming Tang, Rui Zhang, Min-Yen Kan |
| 2024 | User Consented Federated Recommender System Against Personalized Attribute Inference Attack. Qi Hu, Yangqiu Song |
| 2024 | Using Causal Inference to Solve Uncertainty Issues in Dataset Shift. Song Shuang, Muhammad Syafiq Bin Mohd Pozi |
| 2024 | Vector Search with OpenAI Embeddings: Lucene Is All You Need. Jasper Xian, Tommaso Teofili, Ronak Pradeep, Jimmy Lin |
| 2024 | WSDM 2024 Workshop on Large Language Models for Individuals, Groups, and Society. Michael Bendersky, Cheng Li, Qiaozhu Mei, Vanessa Murdock, Jie Tang, Hongning Wang, Hamed Zamani, Mingyang Zhang |
| 2024 | WSDM 2024 Workshop on Representation Learning & Clustering. Lazhar Labiod, Mohamed Nadif, Aghiles Salah |
| 2024 | What I Learned from Spending a Dozen Years in the Dark Web. Nicolas Christin |
| 2024 | Wildfire: A Twitter Social Sensing Platform for Layperson. Zeyu Zhang, Zhengyuan Zhu, Haiqi Zhang, Foram Patel, Josue Caraballo, Patrick Hennecke, Chengkai Li |
| 2024 | WordGraph: A Python Package for Reconstructing Interactive Causal Graphical Models from Text Data. Amine Ferdjaoui, Séverine Affeldt, Mohamed Nadif |