Papers by Quoc Viet Hung Nguyen

3 papers
CARER - ClinicAl Reasoning-Enhanced Representation for Temporal Health Risk Prediction (2024.emnlp-main)

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Challenge: Existing deep learning methods require large datasets to achieve high generalizability.
Approach: They propose a framework that enhances deep learning models with clinical rationales derived from medically proficient Large Language Models.
Outcome: The proposed framework outperforms state-of-the-art models on two tasks using two popular EHR datasets by up to 11.2%.
Explainable and Fine-Grained Safeguarding of LLM Multi-Agent Systems via Bi-Level Graph Anomaly Detection (2026.acl-long)

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Challenge: Existing graph anomaly detection methods rely on coarse sentence-level information and overlook fine-grained lexical cues, limiting their reliability and real-world applicability.
Approach: They propose an explainable and fine-grained safeguarding framework for detecting malicious agents in multi-agent systems (MAS) to incorporate both coarse and fine lexical information for anomalous agent identification.
Outcome: Extensive experiments across diverse MAS topologies and attack scenarios demonstrate robust detection performance and strong interpretability of XG-Guard.
Joint Multilingual Knowledge Graph Completion and Alignment (2022.findings-emnlp)

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Challenge: Existing work on multilingual KG completion has focused on entity and relation alignments, but understanding of how it can aid multilingual alignments is limited.
Approach: They propose to combine two components that jointly accomplish KG completion and alignment.
Outcome: The proposed model outperforms existing competitive baselines on a public multilingual benchmark and achieves state-of-the-art results.

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