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20242026
most citedLarge language models in 6G security: challenges and opportunities

8 citations · 9 across the 9 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.CL2025

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…

cs.LG2025

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…

cs.AI2025

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…

cs.CL2025

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…

cs.NE2025

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…

cs.LG2025★ 1 cited

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…