Jun Yin

Orcid: 0009-0004-6714-3476

Affiliations:

Central South University, Department of Computer Science, Changsha, Hunan, China

According to our database¹, Jun Yin authored at least 21 papers between 2016 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Bibliography

2026

Beyond the Aggregation Dilemma: Prior-Retaining Decoupled Learning for Multimodal Graphs.

[BibT_eX]

[DOI]

CoRR, May, 2026

Echoes in Filter Bubble: Diagnosing and Curing Popularity Bias in Generative Recommenders.

[BibT_eX]

[DOI]

CoRR, May, 2026

Rel-MOSS: Towards Imbalanced Relational Deep Learning on Relational Databases.

[BibT_eX]

[DOI]

CoRR, March, 2026

SimGR: Escaping the Pitfalls of Generative Decoding in LLM-based Recommendation.

[BibT_eX]

[DOI]

CoRR, February, 2026

PS<sup>2</sup>: Parameterized Control for Fine-Grained Student Proficiency Simulation.

[BibT_eX]

[DOI]

CoRR, February, 2026

2025

Have Our Cake and Eat It: Augmentation Diversity and Semantic Consistency Balanced Graph Contrastive Learning.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2025

Unleash LLMs Potential for Sequential Recommendation by Coordinating Dual Dynamic Index Mechanism.

[BibT_eX]

[DOI]

Proceedings of the ACM on Web Conference 2025, 2025

MoKGNN: Boosting Graph Neural Networks via Mixture of Generic and Task-Specific Language Models.

[BibT_eX]

[DOI]

Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, 2025

When Graph Meets Multimodal: Benchmarking and Meditating on Multimodal Attributed Graph Learning.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

2024

When Graph meets Multimodal: Benchmarking on Multimodal Attributed Graphs Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Unleash LLMs Potential for Recommendation by Coordinating Twin-Tower Dynamic Semantic Token Generator.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Adversarial Hard Negative Generation for Complementary Graph Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Hierarchical Graph Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Comprehensive Study on Text-attributed Graphs: Benchmarking and Rethinking.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

V-InFoR: A Robust Graph Neural Networks Explainer for Structurally Corrupted Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021

Leveraging multi-level dependency of relational sequences for social spammer detection.

[BibT_eX]

[DOI]

Neurocomputing, 2021

2019

Prediction and Analysis of Rumour's Impact on Social Media.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Behavioral, 2019

2018

Knowledge-Based Recommendation with Hierarchical Collaborative Embedding.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Social Spammer Detection: A Multi-Relational Embedding Approach.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

2016

Parallelizing K-Means-Based Clustering on Spark.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Advanced Cloud and Big Data, 2016

Jun Yin

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Bibliography

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