5 papers
Vmem-: Low-Compute Out-of-Distribution Detection in Spiking Neural Networks from Membrane-Potential Statistics
Arul Rana, Agrim Tripathi, Shoaib Ahmed Dipu +3
Spiking Neural Networks (SNNs) offer an energy-efficient approach to processing event-camera data, yet out-of-distribution (OOD) detection remains challenging in this setting. Exis…
Stealth Is a Relation, Not a Property: How Event Representations Create Blind Spots for Timing Attacks in Event-Based Perception
Shoaib Ahmed Dipu, Md. Shaown Miah, Kamrul Hasan +1
An event camera produces an asynchronous stream, but what is visible in that stream depends on how a downstream consumer, such as a model or detector, processes time. The same time…
Neural Succession: A Mesoscopic Theory of Invasion, Coexistence, and Stabilization in Continual Learning
Shoaib Ahmed Dipu, Md Salman Shamil, Sayeed Shafayet Chowdhury
Continual learning is usually studied through mechanisms that preserve old knowledge. We develop Successional Learning Theory (SLT), a mesoscopic account in which the current repre…
RIPE-MambaSpike: Resolution-Independent Spiking-State-Space Interfaces for Parameter-Efficient Event-Based Vision
Md Muhiminul Islam, Shoaib Ahmed Dipu, Sayeed Shafayet Chowdhury
Spiking-Mamba hybrids reach strong accuracy on event-based vision, but existing designs often require tens of millions of parameters. Much of that cost comes from how the spiking f…
Exploring and Mitigating Gender Bias in Encoder-Based Transformer Models
Ariyan Hossain, Khondokar Mohammad Ahanaf Hannan, Rakinul Haque +4
Gender bias in language models has gained increasing attention in the field of natural language processing. Encoder-based transformer models, which have achieved state-of-the-art p…