3 papers
cs.CL2026
FAID: Fine-Grained AI-Generated Text Detection Using Multi-Task Auxiliary and Multi-Level Contrastive Learning
Minh Ngoc Ta, Dong Cao Van, Duc-Anh Hoang +6
The growing collaboration between humans and AI models in generative tasks has introduced new challenges in distinguishing between human-written, LLM-generated, and human-LLM colla…
cs.CV2025
More Reliable Pseudo-labels, Better Performance: A Generalized Approach to Single Positive Multi-label Learning
Luong Tran, Thieu Vo, Anh Nguyen +2
Multi-label learning is a challenging computer vision task that requires assigning multiple categories to each image. However, fully annotating large-scale datasets is often imprac…
cs.CL2024
SemiKong: Curating, Training, and Evaluating A Semiconductor Industry-Specific Large Language Model
Christopher Nguyen, William Nguyen, Atsushi Suzuki +10
Large Language Models (LLMs) have demonstrated the potential to address some issues within the semiconductor industry. However, they are often general-purpose models that lack the…