{"total":166,"rows":[{"id":"2101.11427","title":"One Model to Serve All: Star Topology Adaptive Recommender for Multi-Domain CTR Prediction","created":"2021-01-27","cited_by_count":78,"area":null},{"id":"2204.05125","title":"ESCM$^2$: Entire Space Counterfactual Multi-Task Model for Post-Click Conversion Rate Estimation","created":"2022-04-03","cited_by_count":47,"area":null},{"id":"2105.08489","title":"Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising","created":"2021-05-18","cited_by_count":39,"area":null},{"id":"2203.06801","title":"MetaBalance: Improving Multi-Task Recommendations via Adapting Gradient Magnitudes of Auxiliary Tasks","created":"2022-03-14","cited_by_count":34,"area":null},{"id":"2209.06053","title":"Towards Understanding the Overfitting Phenomenon of Deep Click-Through Rate Prediction Models","created":"2022-09-04","cited_by_count":33,"area":null},{"id":"2211.15055","title":"AdaTask: A Task-aware Adaptive Learning Rate Approach to Multi-task Learning","created":"2022-11-28","cited_by_count":31,"area":null},{"id":"2407.16357","title":"TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou","created":"2024-07-23","cited_by_count":30,"area":null},{"id":"2105.13623","title":"Enhanced Doubly Robust Learning for Debiasing Post-click Conversion Rate Estimation","created":"2021-05-28","cited_by_count":28,"area":null},{"id":"2301.12618","title":"ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning","created":"2023-01-30","cited_by_count":28,"area":null},{"id":"2308.12029","title":"Dual-Balancing for Multi-Task Learning","created":"2023-08-23","cited_by_count":27,"area":null},{"id":"2302.03328","title":"Multi-Task Recommendations with Reinforcement Learning","created":"2023-02-07","cited_by_count":26,"area":null},{"id":"2110.06475","title":"SAR-Net: A Scenario-Aware Ranking Network for Personalized Fair Recommendation in Hundreds of Travel Scenarios","created":"2021-10-13","cited_by_count":23,"area":null},{"id":"2104.09713","title":"Hierarchically Modeling Micro and Macro Behaviors via Multi-Task Learning for Conversion Rate Prediction","created":"2021-04-20","cited_by_count":21,"area":null},{"id":"2104.14121","title":"Real Negatives Matter: Continuous Training with Real Negatives for Delayed Feedback Modeling","created":"2021-04-29","cited_by_count":20,"area":null},{"id":"2308.13537","title":"STEM: Unleashing the Power of Embeddings for Multi-task Recommendation","created":"2023-08-16","cited_by_count":19,"area":null},{"id":"2211.06684","title":"A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction","created":"2022-11-12","cited_by_count":18,"area":null},{"id":"2304.09085","title":"Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations","created":"2023-04-17","cited_by_count":18,"area":null},{"id":"2207.09920","title":"DESCN: Deep Entire Space Cross Networks for Individual Treatment Effect Estimation","created":"2022-07-19","cited_by_count":16,"area":null},{"id":"2402.13750","title":"Breaking the Barrier: Utilizing Large Language Models for Industrial Recommendation Systems through an Inferential Knowledge Graph","created":"2024-02-21","cited_by_count":16,"area":null},{"id":"2101.02342","title":"User Response Prediction in Online Advertising","created":"2021-01-07","cited_by_count":15,"area":null},{"id":"2105.08909","title":"Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction","created":"2021-05-19","cited_by_count":13,"area":null},{"id":"2207.03051","title":"A Large Scale Search Dataset for Unbiased Learning to Rank","created":"2022-07-07","cited_by_count":13,"area":null},{"id":"2210.11039","title":"Entire Space Counterfactual Learning for Reliable Content Recommendations","created":"2022-10-20","cited_by_count":13,"area":null},{"id":"2412.20211","title":"Generative Regression Based Watch Time Prediction for Short-Video Recommendation","created":"2024-12-28","cited_by_count":13,"area":null},{"id":"2308.12729","title":"Out of the Box Thinking: Improving Customer Lifetime Value Modelling via Expert Routing and Game Whale Detection","created":"2023-08-24","cited_by_count":11,"area":null},{"id":"2201.12666","title":"Challenges and approaches to privacy preserving post-click conversion prediction","created":"2022-01-29","cited_by_count":10,"area":null},{"id":"2205.14321","title":"Automatic Expert Selection for Multi-Scenario and Multi-Task Search","created":"2022-05-28","cited_by_count":9,"area":null},{"id":"2302.05031","title":"Feature Decomposition for Reducing Negative Transfer: A Novel Multi-task Learning Method for Recommender System","created":"2023-02-10","cited_by_count":9,"area":null},{"id":"2403.12660","title":"ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems","created":"2024-03-19","cited_by_count":9,"area":null},{"id":"2205.07295","title":"Posterior Probability Matters: Doubly-Adaptive Calibration for Neural Predictions in Online Advertising","created":"2022-05-15","cited_by_count":8,"area":null},{"id":"2305.12837","title":"Capturing Conversion Rate Fluctuation during Sales Promotions: A Novel Historical Data Reuse Approach","created":"2023-05-22","cited_by_count":8,"area":null},{"id":"2406.17182","title":"Debiased Recommendation with Noisy Feedback","created":"2024-06-24","cited_by_count":8,"area":null},{"id":"2408.08585","title":"OptDist: Learning Optimal Distribution for Customer Lifetime Value Prediction","created":"2024-08-16","cited_by_count":8,"area":null},{"id":"2107.14768","title":"Debiased Explainable Pairwise Ranking from Implicit Feedback","created":"2021-07-30","cited_by_count":7,"area":null},{"id":"2208.11457","title":"Scenario-Adaptive and Self-Supervised Model for Multi-Scenario Personalized Recommendation","created":"2022-08-24","cited_by_count":7,"area":null},{"id":"2305.18431","title":"Optimizing Airbnb Search Journey with Multi-task Learning","created":"2023-05-28","cited_by_count":7,"area":null},{"id":"2306.16732","title":"Multi-Scenario Ranking with Adaptive Feature Learning","created":"2023-06-29","cited_by_count":7,"area":null},{"id":"2307.11096","title":"Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking","created":"2023-07-12","cited_by_count":7,"area":null},{"id":"2308.05508","title":"Multi-domain Recommendation with Embedding Disentangling and Domain Alignment","created":"2023-08-10","cited_by_count":7,"area":null},{"id":"2402.03379","title":"Entire Chain Uplift Modeling with Context-Enhanced Learning for Intelligent Marketing","created":"2024-02-04","cited_by_count":7,"area":null},{"id":"2108.13592","title":"Zero Shot on the Cold-Start Problem: Model-Agnostic Interest Learning for Recommender Systems","created":"2021-08-31","cited_by_count":6,"area":null},{"id":"2305.08328","title":"FedAds: A Benchmark for Privacy-Preserving CVR Estimation with Vertical Federated Learning","created":"2023-05-15","cited_by_count":6,"area":null},{"id":"2402.14230","title":"MerRec: A Large-scale Multipurpose Mercari Dataset for Consumer-to-Consumer Recommendation Systems","created":"2024-02-22","cited_by_count":6,"area":null},{"id":"2412.08604","title":"Preference Discerning with LLM-Enhanced Generative Retrieval","created":"2024-12-11","cited_by_count":6,"area":null},{"id":"2505.02120","title":"Tricolore: Multi-Behavior User Profiling for Enhanced Candidate Generation in Recommender Systems","created":"2025-05-04","cited_by_count":6,"area":null},{"id":"2106.07356","title":"Mixture of Virtual-Kernel Experts for Multi-Objective User Profile Modeling","created":"2021-06-04","cited_by_count":5,"area":null},{"id":"2108.13475","title":"An Analysis Of Entire Space Multi-Task Models For Post-Click Conversion Prediction","created":"2021-08-18","cited_by_count":5,"area":null},{"id":"2308.05996","title":"Deep Task-specific Bottom Representation Network for Multi-Task Recommendation","created":"2023-08-11","cited_by_count":5,"area":null},{"id":"2508.15217","title":"See Beyond a Single View: Multi-Attribution Learning Leads to Better Conversion Rate Prediction","created":"2025-08-21","cited_by_count":5,"area":null},{"id":"2112.13753","title":"MetaCVR: Conversion Rate Prediction via Meta Learning in Small-Scale Recommendation Scenarios","created":"2021-12-27","cited_by_count":4,"area":null},{"id":"2210.07770","title":"Towards Trustworthy AI-Empowered Real-Time Bidding for Online Advertisement Auctioning","created":"2022-09-21","cited_by_count":4,"area":null},{"id":"2302.01255","title":"adSformers: Personalization from Short-Term Sequences and Diversity of Representations in Etsy Ads","created":"2023-02-02","cited_by_count":4,"area":null},{"id":"2302.02636","title":"Hybrid Contrastive Constraints for Multi-Scenario Ad Ranking","created":"2023-02-06","cited_by_count":4,"area":null},{"id":"2310.08039","title":"Rethinking Large-scale Pre-ranking System: Entire-chain Cross-domain Models","created":"2023-10-12","cited_by_count":4,"area":null},{"id":"2401.04338","title":"G-Meta: Distributed Meta Learning in GPU Clusters for Large-Scale Recommender Systems","created":"2024-01-09","cited_by_count":4,"area":null},{"id":"2401.09507","title":"Deep Ensemble Shape Calibration: Multi-Field Post-hoc Calibration in Online Advertising","created":"2024-01-17","cited_by_count":4,"area":null},{"id":"2402.14399","title":"Ensure Timeliness and Accuracy: A Novel Sliding Window Data Stream Paradigm for Live Streaming Recommendation","created":"2024-02-22","cited_by_count":4,"area":null},{"id":"2405.05606","title":"Optimizing E-commerce Search: Toward a Generalizable and Rank-Consistent Pre-Ranking Model","created":"2024-05-09","cited_by_count":4,"area":null},{"id":"2405.15403","title":"Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random","created":"2024-05-24","cited_by_count":4,"area":null},{"id":"2406.10517","title":"ADSNet: Cross-Domain LTV Prediction with an Adaptive Siamese Network in Advertising","created":"2024-06-15","cited_by_count":4,"area":null},{"id":"2502.03041","title":"Large Language Model as Universal Retriever in Industrial-Scale Recommender System","created":"2025-02-05","cited_by_count":4,"area":null},{"id":"2209.01009","title":"Physics-informed MTA-UNet: Prediction of Thermal Stress and Thermal Deformation of Satellites","created":"2022-09-01","cited_by_count":3,"area":null},{"id":"2211.12105","title":"AdaptDHM: Adaptive Distribution Hierarchical Model for Multi-Domain CTR Prediction","created":"2022-11-22","cited_by_count":3,"area":null},{"id":"2307.09193","title":"ESMC: Entire Space Multi-Task Model for Post-Click Conversion Rate via Parameter Constraint","created":"2023-07-18","cited_by_count":3,"area":null},{"id":"2403.02607","title":"MEBS: Multi-task End-to-end Bid Shading for Multi-slot Display Advertising","created":"2024-03-05","cited_by_count":3,"area":null},{"id":"2403.17425","title":"Masked Multi-Domain Network: Multi-Type and Multi-Scenario Conversion Rate Prediction with a Single Model","created":"2024-03-26","cited_by_count":3,"area":null},{"id":"2409.14682","title":"Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems","created":"2024-09-23","cited_by_count":3,"area":null},{"id":"2209.07574","title":"Towards a Better Microcredit Decision","created":"2022-08-23","cited_by_count":2,"area":null},{"id":"2303.12973","title":"Uncertainty Calibration for Counterfactual Propensity Estimation in Recommendation","created":"2023-03-23","cited_by_count":2,"area":null},{"id":"2304.09176","title":"Enhancing Personalized Ranking With Differentiable Group AUC Optimization","created":"2023-04-17","cited_by_count":2,"area":null},{"id":"2307.05974","title":"Contrastive Learning for Conversion Rate Prediction","created":"2023-07-12","cited_by_count":2,"area":null},{"id":"2401.06406","title":"Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A review","created":"2024-01-12","cited_by_count":2,"area":null},{"id":"2404.19620","title":"Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference","created":"2024-04-30","cited_by_count":2,"area":null},{"id":"2405.01847","title":"A Model-based Multi-Agent Personalized Short-Video Recommender System","created":"2024-05-03","cited_by_count":2,"area":null},{"id":"2410.02791","title":"DifFaiRec: Generative Fair Recommender with Conditional Diffusion Model","created":"2024-09-18","cited_by_count":2,"area":null},{"id":"2410.05806","title":"A Parameter Update Balancing Algorithm for Multi-task Ranking Models in Recommendation Systems","created":"2024-10-08","cited_by_count":2,"area":null},{"id":"2501.14268","title":"Pre-train and Fine-tune: Recommenders as Large Models","created":"2025-01-24","cited_by_count":2,"area":null},{"id":"2503.09492","title":"Learning Cascade Ranking as One Network","created":"2025-03-12","cited_by_count":2,"area":null},{"id":"2506.10520","title":"Macro Graph of Experts for Billion-Scale Multi-Task Recommendation","created":"2025-06-12","cited_by_count":2,"area":null},{"id":"2507.20161","title":"Practical Multi-Task Learning for Rare Conversions in Ad Tech","created":"2025-07-27","cited_by_count":2,"area":null},{"id":"2507.21049","title":"Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning","created":"2025-07-28","cited_by_count":2,"area":null},{"id":"2512.00004","title":"Enhancing Talent Search Ranking with Role-Aware Expert Mixtures and LLM-based Fine-Grained Job Descriptions","created":"2025-10-05","cited_by_count":2,"area":null},{"id":"2601.19965","title":"Modeling Cascaded Delay Feedback for Online Net Conversion Rate Prediction: Benchmark, Insights and Solutions","created":"2026-01-27","cited_by_count":2,"area":null},{"id":"2602.11780","title":"RELATE: A Reinforcement Learning-Enhanced LLM Framework for Advertising Text Generation","created":"2026-02-12","cited_by_count":2,"area":null},{"id":"2602.11799","title":"Hi-SAM: A Hierarchical Structure-Aware Multi-modal Framework for Large-Scale Recommendation","created":"2026-02-12","cited_by_count":2,"area":null},{"id":"2104.08716","title":"Deep Latent Emotion Network for Multi-Task Learning","created":"2021-04-18","cited_by_count":1,"area":null},{"id":"2107.08598","title":"Learning-To-Ensemble by Contextual Rank Aggregation in E-Commerce","created":"2021-07-19","cited_by_count":1,"area":null},{"id":"2110.13365","title":"Multi-Faceted Hierarchical Multi-Task Learning for a Large Number of Tasks with Multi-dimensional Relations","created":"2021-10-26","cited_by_count":1,"area":null},{"id":"2204.07337","title":"Training Entire-Space Models for Target-oriented Opinion Words Extraction","created":"2022-04-15","cited_by_count":1,"area":null},{"id":"2212.09052","title":"A Better Choice: Entire-space Datasets for Aspect Sentiment Triplet Extraction","created":"2022-12-18","cited_by_count":1,"area":null},{"id":"2303.05847","title":"Gradient Coordination for Quantifying and Maximizing Knowledge Transference in Multi-Task Learning","created":"2023-03-10","cited_by_count":1,"area":null},{"id":"2305.01514","title":"Curriculum Modeling the Dependence among Targets with Multi-task Learning for Financial Marketing","created":"2023-04-25","cited_by_count":1,"area":null},{"id":"2305.14103","title":"Simulating News Recommendation Ecosystem for Fun and Profit","created":"2023-05-23","cited_by_count":1,"area":null},{"id":"2308.03855","title":"Mobile Supply: The Last Piece of Jigsaw of Recommender System","created":"2023-08-07","cited_by_count":1,"area":null},{"id":"2308.07857","title":"Impression-Aware Recommender Systems","created":"2023-08-15","cited_by_count":1,"area":null},{"id":"2309.04802","title":"CPMR: Context-Aware Incremental Sequential Recommendation with Pseudo-Multi-Task Learning","created":"2023-09-09","cited_by_count":1,"area":null},{"id":"2311.06777","title":"Alleviating Behavior Data Imbalance for Multi-Behavior Graph Collaborative Filtering","created":"2023-11-12","cited_by_count":1,"area":null},{"id":"2404.08361","title":"Large-Scale Multi-Domain Recommendation: an Automatic Domain Feature Extraction and Personalized Integration Framework","created":"2024-04-12","cited_by_count":1,"area":null},{"id":"2406.00779","title":"Differentiation of Multi-objective Data-driven Decision Pipeline","created":"2024-06-02","cited_by_count":1,"area":null},{"id":"2411.09705","title":"Residual Multi-Task Learner for Applied Ranking","created":"2024-10-30","cited_by_count":1,"area":null}],"next_cursor":"100"}