Junda Ye

Orcid: 0000-0002-2900-4908

According to our database1, Junda Ye authored at least 25 papers between 2022 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Graph-Based Approaches and Functionalities in Retrieval-Augmented Generation: A Comprehensive Survey.
ACM Comput. Surv., July, 2026

Representing Tuple in Graph with Trail Structure.
ACM Trans. Knowl. Discov. Data, April, 2026

Multi-Domain Riemannian Graph Gluing for Building Graph Foundation Models.
CoRR, March, 2026

RoLED: Role-disentangled graph neural network for both homophily and heterophily.
Neurocomputing, 2026

Towards Multifaceted Graph Condensation in Discrete Realm.
Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, 2026

Learning to Explore: Policy-Guided Outlier Synthesis for Graph Out-of-Distribution Detection.
Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025
MoSE: Unveiling Structural Patterns in Graphs via Mixture of Subgraph Experts.
CoRR, September, 2025

Efficiently Transfer User Profile Across Networks.
IEEE Trans. Big Data, February, 2025

CLEAR: Cluster-based Prompt Learning on Heterogeneous Graphs.
CoRR, February, 2025

CLEAR: Cluster-Based Prompt Learning on Heterogeneous Graphs.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2025

Trace: Structural Riemannian Bridge Matching for Transferable Source Localization in Information Propagation.
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

2024
Contrastive sequential interaction network learning on co-evolving Riemannian spaces.
Int. J. Mach. Learn. Cybern., April, 2024

RicciNet: Deep Clustering via A Riemannian Generative Model.
Proceedings of the ACM on Web Conference 2024, 2024

A Mixed-Curvature Graph Diffusion Model.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
GroupAligner: A Deep Reinforcement Learning with Domain Adaptation for Social Group Alignment.
ACM Trans. Web, August, 2023

Contrastive Graph Clustering in Curvature Spaces.
CoRR, 2023

SINCERE: Sequential Interaction Networks representation learning on Co-Evolving RiEmannian manifolds.
Proceedings of the ACM Web Conference 2023, 2023

CONGREGATE: Contrastive Graph Clustering in Curvature Spaces.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing.
Proceedings of the IEEE International Conference on Data Mining, 2023

Self-Supervised Continual Graph Learning in Adaptive Riemannian Spaces.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
DiriE: Knowledge Graph Embedding with Dirichlet Distribution.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

AISFG: Abundant Information Slot Filling Generator.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Privacy-Preserving Vertical Federated Logistic Regression without Trusted Third-Party Coordinator.
Proceedings of the ICMLSC 2022: The 6th International Conference on Machine Learning and Soft Computing, Haikou, China, January 15, 2022

A Self-supervised Riemannian GNN with Time Varying Curvature for Temporal Graph Learning.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

A Self-Supervised Mixed-Curvature Graph Neural Network.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022


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