Kay Liu

Orcid: 0000-0002-2022-9465

According to our database1, Kay Liu authored at least 20 papers between 2022 and 2025.

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

Timeline

Legend:

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Online presence:

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Bibliography

2025
TestNUC: Enhancing Test-Time Computing Approaches through Neighboring Unlabeled Data Consistency.
CoRR, February, 2025

LEGO-Learn: Label-Efficient Graph Open-Set Learning.
Trans. Mach. Learn. Res., 2025

Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement.
Trans. Mach. Learn. Res., 2025

TGTOD: A Global Temporal Graph Transformer for Outlier Detection at Scale.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2025

BANGS: Game-theoretic Node Selection for Graph Self-Training.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

TestNUC: Enhancing Test-Time Computing Approaches and Scaling through Neighboring Unlabeled Data Consistency.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024
Uncertainty in Graph Neural Networks: A Survey.
Trans. Mach. Learn. Res., 2024

CoSENT: Consistent Sentence Embedding via Similarity Ranking.
IEEE ACM Trans. Audio Speech Lang. Process., 2024

PyGOD: A Python Library for Graph Outlier Detection.
J. Mach. Learn. Res., 2024

LEGO-Learn: Label-Efficient Graph Open-Set Learning.
CoRR, 2024

FedGraph: A Research Library and Benchmark for Federated Graph Learning.
CoRR, 2024

Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks.
CoRR, 2024

Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction.
CoRR, 2024

Multitask Active Learning for Graph Anomaly Detection.
CoRR, 2024

Data Augmentation for Supervised Graph Outlier Detection via Latent Diffusion Models.
Proceedings of the Learning on Graphs Conference, 26-29 November 2024, Virtual., 2024

2023
Data Augmentation for Supervised Graph Outlier Detection with Latent Diffusion Models.
CoRR, 2023

Equal Opportunity of Coverage in Fair Regression.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Benchmarking Node Outlier Detection on Graphs.
CoRR, 2022

PyGOD: A Python Library for Graph Outlier Detection.
CoRR, 2022

BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022


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