MTL Recommendation paper list

• 以下将推荐系统中的多任务学习论文分为以下几类：可解释性（Interpretability）、多行为（Multi-behavior）、点击率预测（CTR&CVR）、算法（Algorithm）、Survey、其他。

• 整理了少部分 NLP 与 CV 中的多任务学习论文。

• 另外，有几篇 SIGIR 2022 工作还未公开, 先列举在下面。

Interpretability

• Why I like it: multi-task learning for recommendation and explanation. RecSys 2018

• Explainable recommendation via multi-task learning in opinionated text data. SIGIR 2018

• Co-attentive multi-task learning for explainable recommendation. IJCAI 2019

Multi-behavior (click / buy / like)

• Rank and rate: multi-task learning for recommender systems. RecSys 2018

• Modeling task relationships in multi-task learning with multi-gate mixture-of-experts. KDD 2018

• Multiple relational attention network for multi-task learning. SIGKDD 2019

• Recommending what video to watch next: a multitask ranking system. RecSys 2019

• Predicting different types of conversions with multi-task learning in online advertising. SIGKDD 2019

• Cross-Task Knowledge Distillation in Multi-Task Recommendation. AAAI 2022

• MetaBalance: Improving Multi-Task Recommendations via Adapting Gradient Magnitudes of Auxiliary Tasks. WWW 2022

CTR CVR

• Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate SIGIR 2018

• Progressive Layered Extraction (PLE): A Novel Multi-Task Learning (MTL) Model for Personalized Recommendations. RecSys 2020

• LT4REC: A Lottery Ticket Hypothesis Based Multi-task Practice for Video Recommendation System. arxiv 2021

• A Contrastive Sharing Model for Multi-Task Recommendation. WWW 2022

其他

• Online multitask collaborative filtering for on-the-fly recommender systems. RecSys 2013

• Ask the gru: Multitask learning for deep text recommendations. RecSys 2016

• Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering. WWW 2022

Algorithm

• Cross-stitch networks for multi-task learning. CVPR 2016

• Deep multi-task representation learning: A tensor factorisation approach ICLR 2017

• Learning Sparse Sharing Architectures for Multiple Tasks. AAAI 2020

• Adversarial Robustness in Multi-Task Learning: Promises and Illusions AAAI 2022

• Improving Evidential Deep Learning via Multi-Task Learning. AAAI 2022

Survey

• A Survey on Multi-Task Learning. TKDE 2021

CV

• Faster r-cnn: Towards real-time object detection with region proposal networks. NIPS

• Taskonomy: Disentangling Task Transfer Learning CVPR 2018

• SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning. AAAI 2019

NLP

• A unified architecture for natural language processing: Deep neural networks with multitask learning. ICML 2008

• Multitask deep neural networks for natural language understanding.

• Multi-task sequence to sequence learning. ICLR 2016

未公开

• Diversity vs Relevance: a practical multi-objective study in luxury fashion recommendations. SIGIR 2022

• Hierarchical Multi-Task Graph Recurrent Network for Next POI Recommendation. SIGIR 2022

• Towards Results-level Proportionality for Multi-objective Recommender Systems. SIGIR 2022