Shuang Zhou

Orcid: 0000-0001-5739-1637

Affiliations:
  • Hong Kong Polytechnic University, Hong Kong


According to our database1, Shuang Zhou authored at least 21 papers between 2020 and 2025.

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Bibliography

2025
Automating Expert-Level Medical Reasoning Evaluation of Large Language Models.
CoRR, July, 2025

AnyMAC: Cascading Flexible Multi-Agent Collaboration via Next-Agent Prediction.
CoRR, June, 2025

Uncertainty-Aware Large Language Models for Explainable Disease Diagnosis.
CoRR, May, 2025

Retrieval-augmented in-context learning for multimodal large language models in disease classification.
CoRR, May, 2025

EPEE: Towards Efficient and Effective Foundation Models in Biomedicine.
CoRR, March, 2025

An evaluation of DeepSeek Models in Biomedical Natural Language Processing.
CoRR, March, 2025

MMRAG: Multi-Mode Retrieval-Augmented Generation with Large Language Models for Biomedical In-Context Learning.
CoRR, February, 2025

Continually Evolved Multimodal Foundation Models for Cancer Prognosis.
CoRR, January, 2025

RAMIE: retrieval-augmented multi-task information extraction with large language models on dietary supplements.
J. Am. Medical Informatics Assoc., 2025

Open-Set Cross-Network Node Classification via Unknown-Excluded Adversarial Graph Domain Alignment.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
Open-world electrocardiogram classification via domain knowledge-driven contrastive learning.
Neural Networks, 2024

Large Language Models for Disease Diagnosis: A Scoping Review.
CoRR, 2024

Interpretable Differential Diagnosis with Dual-Inference Large Language Models.
CoRR, 2024

Graph Anomaly Detection with Noisy Labels by Reinforcement Learning.
CoRR, 2024

Denoising-Aware Contrastive Learning for Noisy Time Series.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Enhancing Explainable Rating Prediction through Annotated Macro Concepts.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation.
IEEE Trans. Knowl. Data Eng., December, 2023

Interest Driven Graph Structure Learning for Session-Based Recommendation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

2022
Unseen Anomaly Detection on Networks via Multi-Hypersphere Learning.
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

2021
Subtractive Aggregation for Attributed Network Anomaly Detection.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
PHICON: Improving Generalization of Clinical Text De-identification Models via Data Augmentation.
Proceedings of the 3rd Clinical Natural Language Processing Workshop, 2020


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