8 papers
LLM as Detector: An In-context Learning Approach for Tabular Anomaly Detection
Tu Anh Hoang Nguyen, Dang Nguyen, Thuc Duy Le +2
Anomaly detection in tabular data is challenging because abnormal samples often arise as violations of cross-feature dependencies rather than simple marginal deviations. Existing d…
TAKE: Trajectory-Aware Knowledge Estimation for Text Dataset Distillation
Tri-Nhan Vo, Dang Nguyen, Sunil Gupta
Large-scale text corpora have become a quiet bottleneck in modern NLP, not just in storage, but in the accumulated cost of training, fine-tuning, and continual learning. We propose…
Improving Diversity in Black-box Few-shot Knowledge Distillation
Tri-Nhan Vo, Dang Nguyen, Kien Do +1
Knowledge distillation (KD) is a well-known technique to effectively compress a large network (teacher) to a smaller network (student) with little sacrifice in performance. However…
High-dimensional Level Set Estimation with Trust Regions and Double Acquisition Functions
Giang Ngo, Dat Phan Trong, Dang Nguyen +1
Level set estimation (LSE) classifies whether an unknown function's value exceeds a specified threshold for given inputs, a fundamental problem in many real-world applications. In…
Taint-Based Code Slicing for LLMs-based Malicious NPM Package Detection
Dang-Khoa Nguyen, Gia-Thang Ho, Quang-Minh Pham +5
Software supply chain attacks on the npm ecosystem have grown increasingly sophisticated, exploiting obfuscation and complex logic to evade detection. Large Language Models (LLMs)…
Causal-Aware Tabular GANs with Reinforcement Learning
Tu Anh Hoang Nguyen, Dang Nguyen, Tri-Nhan Vo +3
Existing tabular data generation methods primarily focus on matching statistical distributions between real and synthetic data, often overlooking the preservation of underlying cau…
Few-shot Algorithm Assurance
Dang Nguyen, Sunil Gupta
In image classification tasks, deep learning models are vulnerable to image distortion. For successful deployment, it is important to identify distortion levels under which the mod…
Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process Prior
Giang Ngo, Dang Nguyen, Sunil Gupta
The objective of active level set estimation for a black-box function is to precisely identify regions where the function values exceed or fall below a specified threshold by itera…