Zhuomin Chen

According to our database1, Zhuomin Chen authored at least 14 papers between 2023 and 2025.

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

Timeline

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Bibliography

2025
From Binary to Continuous: Stochastic Re-Weighting for Robust Graph Explanation.
CoRR, August, 2025

SF<sup>2</sup>Bench: Evaluating Data-Driven Models for Compound Flood Forecasting in South Florida.
CoRR, June, 2025

TSRating: Rating Quality of Diverse Time Series Data by Meta-learning from LLM Judgment.
CoRR, June, 2025

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision.
CoRR, June, 2025

LM<sup>2</sup>otifs : An Explainable Framework for Machine-Generated Texts Detection.
CoRR, May, 2025

F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
Explanation-Preserving Augmentation for Semi-Supervised Graph Representation Learning.
CoRR, 2024

Interpreting Graph Neural Networks with In-Distributed Proxies.
CoRR, 2024

RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

TimeX++: Learning Time-Series Explanations with Information Bottleneck.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
TSNN: A Topic and Structure Aware Neural Network for Rumor Detection.
Neurocomputing, April, 2023

RegExplainer: Generating Explanations for Graph Neural Networks in Regression Task.
CoRR, 2023


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