4 papers · 1 filter
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…
Causal-Aware Generative Adversarial Networks with Reinforcement Learning
Tu Anh Hoang Nguyen, Dang Nguyen, Tri-Nhan Vo +2
The utility of tabular data for tasks ranging from model training to large-scale data analysis is often constrained by privacy concerns or regulatory hurdles. While existing data g…
Rethinking Large Language Model Distillation: A Constrained Markov Decision Process Perspective
Matthieu Zimmer, Xiaotong Ji, Tu Nguyen +1
We introduce a novel approach to large language model (LLM) distillation by formulating it as a constrained reinforcement learning problem. While recent work has begun exploring th…
Noise Contrastive Estimation-based Matching Framework for Low-Resource Security Attack Pattern Recognition
Tu Nguyen, Nedim Šrndić, Alexander Neth
Tactics, Techniques and Procedures (TTPs) represent sophisticated attack patterns in the cybersecurity domain, described encyclopedically in textual knowledge bases. Identifying TT…