68 citations · 87 across the 20 of their papers we have counts for
22 papers
PPO-HRAP: Proximal Policy Optimization with a Hybrid Regime-Aware Policy for Risk-Controlled Trading
Duong Hien Chi Kien, Thanh Trung Huynh
Reinforcement learning for trading often struggles to balance upside participation with drawdown control. Profit-only policies can collapse toward passive long exposure on upward-d…
Nonparametric Distribution Matching for Self-Supervised Whole-Slide Image Condensation
Duong M. Nguyen, Trong Nghia Hoang, Hang Thi Nguyen +3
Histological whole-slide images (WSIs) are central to computational pathology but pose severe computational challenges due to their extremely high resolution, often spanning severa…
SCENARIODIFF: A Scenario-level Guidance Framework for Multimodal Time Series Forecasting--Extended Version
Tuan-Binh Tran, Dat Nguyen Cong, Duc-Trong Le +2
Textual context such as news, reports, and logs can provide valuable signals for time series forecasting, especially when future dynamics are driven by external events that are not…
Improving Federated Graph Recommendation with Semantic Guidance
Thi Minh Chau Nguyen, Hien Trang Nguyen, Duc Anh Nguyen +3
Graph-based recommendation models effectively capture high-order collaborative signals from user--item interaction graphs. Federated learning (FL) enables privacy-preserving traini…
FINER-SQL: Boosting Small Language Models for Text-to-SQL
Thanh Dat Hoang, Thanh Trung Huynh, Matthias Weidlich +4
Large language models have driven major advances in Text-to-SQL generation. However, they suffer from high computational cost, long latency, and data privacy concerns, which make t…
Empowering Contrastive Federated Sequential Recommendation with LLMs
Thi Minh Chau Nguyen, Minh Hieu Nguyen, Duc Anh Nguyen +3
Federated sequential recommendation (FedSeqRec) aims to perform next-item prediction while keeping user data decentralised, yet model quality is frequently constrained by fragmente…
Federated Prompt-Tuning with Heterogeneous and Incomplete Multimodal Client Data
Thu Hang Phung, Duong M. Nguyen, Thanh Trung Huynh +3
This paper introduces a generalized federated prompt-tuning framework for practical scenarios where local datasets are multi-modal and exhibit different distributional patterns of…
A Multi-agent Text2SQL Framework using Small Language Models and Execution Feedback
Thanh Dat Hoang, Thanh Trung Huynh, Matthias Weidlich +4
Text2SQL, the task of generating SQL queries from natural language text, is a critical challenge in data engineering. Recently, Large Language Models (LLMs) have demonstrated super…
Scaling Text2SQL via LLM-efficient Schema Filtering with Functional Dependency Graph Rerankers
Thanh Dat Hoang, Thanh Tam Nguyen, Thanh Trung Huynh +2
Most modern Text2SQL systems prompt large language models (LLMs) with entire schemas -- mostly column information -- alongside the user's question. While effective on small databas…
Learning Reconfigurable Representations for Multimodal Federated Learning with Missing Data
Duong M. Nguyen, Trong Nghia Hoang, Thanh Trung Huynh +2
Multimodal federated learning in real-world settings often encounters incomplete and heterogeneous data across clients. This results in misaligned local feature representations tha…
Instruction-Guided Editing Controls for Images and Multimedia: A Survey in LLM era
Thanh Tam Nguyen, Zhao Ren, Trinh Pham +4
The rapid advancement of large language models (LLMs) and multimodal learning has transformed digital content creation and manipulation. Traditional visual editing tools require si…
FedMAC: Tackling Partial-Modality Missing in Federated Learning with Cross-Modal Aggregation and Contrastive Regularization
Manh Duong Nguyen, Trung Thanh Nguyen, Huy Hieu Pham +3
Federated Learning (FL) is a method for training machine learning models using distributed data sources. It ensures privacy by allowing clients to collaboratively learn a shared gl…
Heterogeneous Hypergraph Embedding for Recommendation Systems
Darnbi Sakong, Viet Hung Vu, Thanh Trung Huynh +4
Recent advancements in recommender systems have focused on integrating knowledge graphs (KGs) to leverage their auxiliary information. The core idea of KG-enhanced recommenders is…
Fast-FedUL: A Training-Free Federated Unlearning with Provable Skew Resilience
Thanh Trung Huynh, Trong Bang Nguyen, Phi Le Nguyen +4
Federated learning (FL) has recently emerged as a compelling machine learning paradigm, prioritizing the protection of privacy for training data. The increasing demand to address i…
Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures
Thanh Toan Nguyen, Quoc Viet Hung Nguyen, Thanh Tam Nguyen +4
Recommender systems have become an integral part of online services to help users locate specific information in a sea of data. However, existing studies show that some recommender…
A Survey of Privacy-Preserving Model Explanations: Privacy Risks, Attacks, and Countermeasures
Thanh Tam Nguyen, Thanh Trung Huynh, Zhao Ren +4
As the adoption of explainable AI (XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and exp…
High Accurate and Explainable Multi-Pill Detection Framework with Graph Neural Network-Assisted Multimodal Data Fusion
Anh Duy Nguyen, Huy Hieu Pham, Huynh Thanh Trung +3
Due to the significant resemblance in visual appearance, pill misuse is prevalent and has become a critical issue, responsible for one-third of all deaths worldwide. Pill identific…
Efficient Integration of Multi-Order Dynamics and Internal Dynamics in Stock Movement Prediction
Thanh Trung Huynh, Minh Hieu Nguyen, Thanh Tam Nguyen +4
Advances in deep neural network (DNN) architectures have enabled new prediction techniques for stock market data. Unlike other multivariate time-series data, stock markets show two…
A Survey of Machine Unlearning
Thanh Tam Nguyen, Thanh Trung Huynh, Zhao Ren +4
Today, computer systems hold large amounts of personal data. Yet while such an abundance of data allows breakthroughs in artificial intelligence, and especially machine learning (M…
Detecting Rumours with Latency Guarantees using Massive Streaming Data
Thanh Tam Nguyen, Thanh Trung Huynh, Hongzhi Yin +4
Today's social networks continuously generate massive streams of data, which provide a valuable starting point for the detection of rumours as soon as they start to propagate. Howe…
Incomplete Knowledge Graph Alignment
Vinh Van Tong, Thanh Trung Huynh, Thanh Tam Nguyen +3
Knowledge graph (KG) alignment - the task of recognizing entities referring to the same thing in different KGs - is recognized as one of the most important operations in the field…
A War Beyond Deepfake: Benchmarking Facial Counterfeits and Countermeasures
Minh Tam Pham, Thanh Trung Huynh, Van Vinh Tong +4
In recent years, visual forgery has reached a level of sophistication that humans cannot identify fraud, which poses a significant threat to information security. A wide range of m…