Jiawei Chen

Orcid: 0000-0002-4752-2629

Affiliations:
  • University of Science and Technology of China, School of Information Science and Technology, Hefei, China
  • Zhejiang University, LianlianPay Joint Research Center, Hangzhou, China (PhD 2020)


According to our database1, Jiawei Chen authored at least 74 papers between 2018 and 2024.

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Bibliography

2024
How graph convolutions amplify popularity bias for recommendation?
Frontiers Comput. Sci., October, 2024

On the Effectiveness of Sampled Softmax Loss for Item Recommendation.
ACM Trans. Inf. Syst., July, 2024

CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System.
ACM Trans. Inf. Syst., January, 2024

Multi-scale self-supervised representation learning with temporal alignment for multi-rate time series modeling.
Pattern Recognit., January, 2024

Knowledge-Enhanced Causal Reinforcement Learning Model for Interactive Recommendation.
IEEE Trans. Multim., 2024

Towards Dynamic Graph Neural Networks with Provably High-Order Expressive Power.
CoRR, 2024

The Devil is in the Sources! Knowledge Enhanced Cross-Domain Recommendation in an Information Bottleneck Perspective.
CoRR, 2024

Conditional Image Synthesis with Diffusion Models: A Survey.
CoRR, 2024

LLM4DSR: Leveraing Large Language Model for Denoising Sequential Recommendation.
CoRR, 2024

Dynamic Graph Transformer with Correlated Spatial-Temporal Positional Encoding.
CoRR, 2024

Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization.
CoRR, 2024

Motif-driven Subgraph Structure Learning for Graph Classification.
CoRR, 2024

Better Late Than Never: Formulating and Benchmarking Recommendation Editing.
CoRR, 2024

Towards a Unified Framework of Clustering-based Anomaly Detection.
CoRR, 2024

Revisiting the Message Passing in Heterophilous Graph Neural Networks.
CoRR, 2024

How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective.
CoRR, 2024

EasyRL4Rec: A User-Friendly Code Library for Reinforcement Learning Based Recommender Systems.
CoRR, 2024

Knowledge Translation: A New Pathway for Model Compression.
CoRR, 2024

Distributionally Robust Graph-based Recommendation System.
Proceedings of the ACM on Web Conference 2024, 2024

EasyRL4Rec: An Easy-to-use Library for Reinforcement Learning Based Recommender Systems.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

SIGformer: Sign-aware Graph Transformer for Recommendation.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

ReLand: Integrating Large Language Models' Insights into Industrial Recommenders via a Controllable Reasoning Pool.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Models.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

BSL: Understanding and Improving Softmax Loss for Recommendation.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Confidence-aware Self-Semantic Distillation on Knowledge Graph Embedding.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

The Devil is in the Sources! Knowledge Enhanced Cross-Domain Recommendation in an Information Bottleneck Perspective.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
Popularity Bias is not Always Evil: Disentangling Benign and Harmful Bias for Recommendation.
IEEE Trans. Knowl. Data Eng., October, 2023

Time-aware Path Reasoning on Knowledge Graph for Recommendation.
ACM Trans. Inf. Syst., April, 2023

Information Retrieval meets Large Language Models: A strategic report from Chinese IR community.
AI Open, January, 2023

Bias and Debias in Recommender System: A Survey and Future Directions.
ACM Trans. Inf. Syst., 2023

SamWalker++: Recommendation With Informative Sampling Strategy.
IEEE Trans. Knowl. Data Eng., 2023

Spatiotemporal Multiscale Correlation Embedding With Process Variable Reorder for Industrial Soft Sensing.
IEEE Trans. Instrum. Meas., 2023

Adap-tau: Adaptively Modulating Embedding Magnitude for Recommendation.
CoRR, 2023

FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion.
CoRR, 2023

On the Theories Behind Hard Negative Sampling for Recommendation.
Proceedings of the ACM Web Conference 2023, 2023

Adap-τ : Adaptively Modulating Embedding Magnitude for Recommendation.
Proceedings of the ACM Web Conference 2023, 2023

Unbiased Knowledge Distillation for Recommendation.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

A Generic Learning Framework for Sequential Recommendation with Distribution Shifts.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Alleviating Matthew Effect of Offline Reinforcement Learning in Interactive Recommendation.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

OpenGSL: A Comprehensive Benchmark for Graph Structure Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding Contrastive Learning via Distributionally Robust Optimization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Discriminative-Invariant Representation Learning for Unbiased Recommendation.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

CDR: Conservative Doubly Robust Learning for Debiased Recommendation.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Homophily-enhanced Structure Learning for Graph Clustering.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Robust Sequence Networked Submodular Maximization.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions.
CoRR, 2022

KuaiRec: A Fully-observed Dataset for Recommender Systems.
CoRR, 2022

Neighboring Backdoor Attacks on Graph Convolutional Network.
CoRR, 2022

On the Effectiveness of Sampled Softmax Loss for Item Recommendation.
CoRR, 2022

IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation.
ACM Trans. Inf. Syst., 2021

Profit maximization for competitive social advertising.
Theor. Comput. Sci., 2021

CausCF: Causal Collaborative Filtering for RecommendationEffect Estimation.
CoRR, 2021

On the Equivalence of Decoupled Graph Convolution Network and Label Propagation.
Proceedings of the WWW '21: The Web Conference 2021, 2021

AutoDebias: Learning to Debias for Recommendation.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Bias Issues and Solutions in Recommender System: Tutorial on the RecSys 2021.
Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Distilling Holistic Knowledge with Graph Neural Networks.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

CausCF: Causal Collaborative Filtering for Recommendation Effect Estimation.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System.
CoRR, 2020

Sparse Causal Residual Neural Network for Linear and Nonlinear Concurrent Causal Inference and Root Cause Diagnosis.
Proceedings of the 16th International Conference on Control, 2020

DGE: Deep Generative Network Embedding Based on Commonality and Individuality.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Fast Adaptively Weighted Matrix Factorization for Recommendation with Implicit Feedback.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Location driven influence maximization: Online spread via offline deployment.
Knowl. Based Syst., 2019

Post and repost: A holistic view of budgeted influence maximization.
Neurocomputing, 2019

Social recommendation based on users' attention and preference.
Neurocomputing, 2019

HAHE: Hierarchical Attentive Heterogeneous Information Network Embedding.
CoRR, 2019

SamWalker: Social Recommendation with Informative Sampling Strategy.
Proceedings of the World Wide Web Conference, 2019

Adaptive Influence Blocking: Minimizing the Negative Spread by Observation-Based Policies.
Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

2018
Social Recommendation with Missing Not at Random Data.
Proceedings of the IEEE International Conference on Data Mining, 2018

Modeling Users' Exposure with Social Knowledge Influence and Consumption Influence for Recommendation.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018


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