2 papers
cs.CV2026
When Generative Augmentation Hurts: A Benchmark Study of GAN and Diffusion Models for Bias Correction in AI Classification Systems
Shesh Narayan Gupta, Nik Bear Brown
Generative models are widely used to compensate for class imbalance in AI training pipelines, yet their failure modes under low-data conditions are poorly understood. This paper re…
cs.RO2024
Advances in Transformers for Robotic Applications: A Review
Nikunj Sanghai, Nik Bear Brown
The introduction of Transformers architecture has brought about significant breakthroughs in Deep Learning (DL), particularly within Natural Language Processing (NLP). Since their…