Zhimeng Guo

Orcid: 0000-0002-3921-7640

According to our database1, Zhimeng Guo authored at least 14 papers between 2021 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability.
Mach. Intell. Res., December, 2024

Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Efficient Contrastive Learning for Fast and Accurate Inference on Graphs.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Jailbreak Open-Sourced Large Language Models via Enforced Decoding.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
On the Safety of Open-Sourced Large Language Models: Does Alignment Really Prevent Them From Being Misused?
CoRR, 2023

Improving Fairness of Graph Neural Networks: A Graph Counterfactual Perspective.
CoRR, 2023

Fairness-aware Message Passing for Graph Neural Networks.
CoRR, 2023

Counterfactual Learning on Graphs: A Survey.
CoRR, 2023

Towards Fair Graph Neural Networks via Graph Counterfactual.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Link Prediction on Heterophilic Graphs via Disentangled Representation Learning.
CoRR, 2022

Decoupled Self-supervised Learning for Non-Homophilous Graphs.
CoRR, 2022

Decoupled Self-supervised Learning for Graphs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Label-Wise Graph Convolutional Network for Heterophilic Graphs.
Proceedings of the Learning on Graphs Conference, 2022

2021
Label-Wise Message Passing Graph Neural Network on Heterophilic Graphs.
CoRR, 2021


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