449 citations · 549 across the 21 of their papers we have counts for
22 papers
An Efficient and Effective Agentic Group Shilling Attack on Recommender Systems
Quoc Viet Nguyen, Trinh Pham, Viet Huynh +4
Recommender systems have become core infrastructure for modern online platforms, personalizing content at scale and strongly influencing what users see, click on, and purchase. How…
EPIC: Explicit Posterior Item Conditioning for Semantic ID Diffusion Recommendation
Tuan-Binh Tran, Thanh Tam Nguyen, Quoc Viet Hung Nguyen +3
Semantic ID (SID) generative recommendation predicts the next item by generating a short tuple of discrete tokens. Recent masked-diffusion methods improve this process through bidi…
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…
AV-SQL: Decomposing Complex Text-to-SQL Queries with Agentic Views
Minh Tam Pham, Trinh Pham, Tong Chen +3
Text-to-SQL is the task of translating natural language queries into executable SQL for a given database, enabling non-expert users to access structured data without writing SQL ma…
An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data
Trinh Pham, Thanh Tam Nguyen, Viet Huynh +2
Recent advances in large language models have strengthened Text2SQL systems that translate natural language questions into database queries. A persistent deployment challenge is to…
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…
Multilingual Text-to-SQL: Benchmarking the Limits of Language Models with Collaborative Language Agents
Khanh Trinh Pham, Thu Huong Nguyen, Jun Jo +2
Text-to-SQL enables natural access to databases, yet most benchmarks are English-only, limiting multilingual progress. We introduce MultiSpider 2.0, extending Spider 2.0 to eight l…
Toward a Vision-Language Foundation Model for Medical Data: Multimodal Dataset and Benchmarks for Vietnamese PET/CT Report Generation
Huu Tien Nguyen, Dac Thai Nguyen, The Minh Duc Nguyen +11
Vision-Language Foundation Models (VLMs), trained on large-scale multimodal datasets, have driven significant advances in Artificial Intelligence (AI) by enabling rich cross-modal…
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…
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…
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…
Model-Agnostic and Diverse Explanations for Streaming Rumour Graphs
Thanh Tam Nguyen, Thanh Cong Phan, Minh Hieu Nguyen +4
The propagation of rumours on social media poses an important threat to societies, so that various techniques for rumour detection have been proposed recently. Yet, existing work f…
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…
Artificial Intelligence in the Battle against Coronavirus (COVID-19): A Survey and Future Research Directions
Thanh Thi Nguyen, Quoc Viet Hung Nguyen, Dung Tien Nguyen +7
Artificial intelligence (AI) has been applied widely in our daily lives in a variety of ways with numerous success stories. AI has also contributed to dealing with the coronavirus…
Deep Learning for Deepfakes Creation and Detection: A Survey
Thanh Thi Nguyen, Quoc Viet Hung Nguyen, Dung Tien Nguyen +6
Deep learning has been successfully applied to solve various complex problems ranging from big data analytics to computer vision and human-level control. Deep learning advances how…