6 papers
HyperZip: Efficient Data Compression through Personalized Diffusion LLMs with Hypernetworks
Thai Nguyen, Khang Tran, NhatHai Phan
Large language models (LLMs) have shown strong potential for lossless data compression, but existing approaches are constrained by the high computational cost and low throughput of…
Poison with Style: A Practical Poisoning Attack on Code Large Language Models
Khang Tran, Yazan Boshmaf, Issa Khalil +3
Code Large Language Models (CLLMs) serve as the core of modern code agents, enabling developers to automate complex software development tasks. In this paper, we present Poison-wit…
Gradient Transformer: Learning to Generate Updates for LLMs
Binh-Nguyen Nguyen, Khang Tran, NhatHai Phan +1
Many organizations lack computational resources to fine-tune large language models (LLMs) on private (unshareable) data for better utility, while fine-tuning tiny language models (…
Program Structure-aware Language Models: Targeted Software Testing beyond Textual Semantics
Khang Tran, Khoa Nguyen, Cristian Borcea +1
Recent advances in large language models for test case generation have improved branch coverage via prompt-engineered mutations. However, they still lack principled mechanisms for…
PRPO: Paragraph-level Policy Optimization for Vision-Language Deepfake Detection
Tuan Nguyen, Naseem Khan, Khang Tran +2
The rapid rise of synthetic media has made deepfake detection a critical challenge for online safety and trust. Progress remains constrained by the scarcity of large, high-quality…
FairDP: Certified Fairness with Differential Privacy
Khang Tran, Ferdinando Fioretto, Issa Khalil +2
This paper introduces FairDP, a novel training mechanism designed to provide group fairness certification for the trained model's decisions, along with a differential privacy (DP)…