9 citations · 20 across the 6 of their papers we have counts for
13 papers
Feature Alignment and Representation Transfer in Knowledge Distillation for Large Language Models
Junjie Yang, Junhao Song, Xudong Han +9
Knowledge distillation (KD) is a technique for transferring knowledge from complex teacher models to simpler student models, significantly enhancing model efficiency and accuracy.…
Active Learning Methods for Efficient Data Utilization and Model Performance Enhancement
Chiung-Yi Tseng, Junhao Song, Ziqian Bi +4
In the era of data-driven intelligence, the paradox of data abundance and annotation scarcity has emerged as a critical bottleneck in the advancement of machine learning. This pape…
Generative Adversarial Networks Bridging Art and Machine Intelligence
Junhao Song, Yichao Zhang, Ziqian Bi +25
Generative Adversarial Networks (GAN) have greatly influenced the development of computer vision and artificial intelligence in the past decade and also connected art and machine i…
From In Silico to In Vitro: A Comprehensive Guide to Validating Bioinformatics Findings
Tianyang Wang, Silin Chen, Yunze Wang +18
The integration of bioinformatics predictions and experimental validation plays a pivotal role in advancing biological research, from understanding molecular mechanisms to developi…
From Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence
Tianyang Wang, Yunze Wang, Jun Zhou +16
Uncertainty quantification (UQ) is a critical aspect of artificial intelligence (AI) systems, particularly in high-risk domains such as healthcare, autonomous systems, and financia…
Deep Learning Model Security: Threats and Defenses
Tianyang Wang, Ziqian Bi, Yichao Zhang +24
Deep learning has transformed AI applications but faces critical security challenges, including adversarial attacks, data poisoning, model theft, and privacy leakage. This survey e…