8 citations · 9 across the 9 of their papers we have counts for
9 papers
PolyAlign: Conditional Human-Distribution Alignment
L. D. M. S. Sai Teja, Ufaq Khan, Sathira Silva +2
Post-training methods such as supervised fine-tuning (SFT) and preference optimization typically align language models toward a single global assistant behavior. While effective fo…
Detecting Jailbreak Attempts in Clinical Training LLMs Through Automated Linguistic Feature Extraction
Tri Nguyen, Huy Hoang Bao Le, Lohith Srikanth Pentapalli +2
Detecting jailbreak attempts in clinical training large language models (LLMs) requires accurate modeling of linguistic deviations that signal unsafe or off-task user behavior. Pri…
VietBinoculars: A Zero-Shot Approach for Detecting Vietnamese LLM-Generated Text
Trieu Hai Nguyen, Sivaswamy Akilesh
The rapid proliferation of Large Language Models has intensified the challenge of distinguishing LLM-generated text from human writing in non-English languages. This study introduc…
Distribution Matching via Generalized Consistency Models
Sagar Shrestha, Rajesh Shrestha, Tri Nguyen +1
Recent advancement in generative models have demonstrated remarkable performance across various data modalities. Beyond their typical use in data synthesis, these models play a cru…
LLM-as-a-Fuzzy-Judge: Fine-Tuning Large Language Models as a Clinical Evaluation Judge with Fuzzy Logic
Weibing Zheng, Laurah Turner, Jess Kropczynski +3
Clinical communication skills are critical in medical education, and practicing and assessing clinical communication skills on a scale is challenging. Although LLM-powered clinical…
Jailbreak Detection in Clinical Training LLMs Using Feature-Based Predictive Models
Tri Nguyen, Lohith Srikanth Pentapalli, Magnus Sieverding +11
Jailbreaking in Large Language Models (LLMs) threatens their safe use in sensitive domains like education by allowing users to bypass ethical safeguards. This study focuses on dete…
Fuzzy Logic -- Based Scheduling System for Part-Time Workforce
Tri Nguyen, Kelly Cohen
This paper explores the application of genetic fuzzy systems to efficiently generate schedules for a team of part-time student workers at a university. Given the preferred number o…
Momentum Contrastive Learning with Enhanced Negative Sampling and Hard Negative Filtering
Duy Hoang, Huy Ngo, Khoi Pham +3
Contrastive learning has become pivotal in unsupervised representation learning, with frameworks like Momentum Contrast (MoCo) effectively utilizing large negative sample sets to e…
Large language models in 6G security: challenges and opportunities
Tri Nguyen, Huong Nguyen, Ahmad Ijaz +3
The rapid integration of Generative AI (GenAI) and Large Language Models (LLMs) in sectors such as education and healthcare have marked a significant advancement in technology. How…