17 papers
A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI
Taye Akinrele, Sindhuja Penchala, Noorbakhsh Amiri Golilarz +2
Cognitive AI seeks to move beyond language generation and autonomous task execution toward systems capable of sustained reasoning, adaptive behavior, persistent memory, and self-re…
Cognitive Firewall: A Proactive, Zero-Trust, Multi-Gate Framework for LLM Safety
Michele Guida, Ruslan Shikhhamzayev, Sindhuja Penchala +4
Large language models (LLMs) can be induced to produce harmful content through multi turn strategies in which no single user message appears clearly unsafe. Existing runtime safegu…
Adaptive Hebbian Memory Routing in Vision Transformers for Few-Shot Learning
Mohammed Yusuf Mujawar, Noorbakhsh Amiri Golilarz
Few-shot image recognition requires models to adapt to new classes from a small labeled support set. Hebbian fast-weight memory can provide temporary associative information during…
From Convolution to Transformer: A Comparative Study of U-Net Variants for Brain Tumor and Retinal Vessel Segmentation
Khoa Pham, Sindhuja Penchala, Jiacheng Li +2
Medical image segmentation plays an important role in computer aided diagnosis, treatment planning, and disease monitoring. U-Net has been widely used for biomedical image segmenta…
Evaluating Transformer and LSTM Frameworks for Prediction in Ungauged Basins
Taye Akinrele, James Halgren, Noorbakhsh Amiri Golilarz +2
Watershed networks exhibit convergent topologies in which multiple tributaries merge into downstream channels,integrating diverse upstream hydrological processes. In ungauged basin…
Where to Bind Matters: Hebbian Fast Weights in Vision Transformers for Few-Shot Character Recognition
Gavin Money, Sindhuja Penchala, Jiacheng Li +1
Standard transformer architectures learn fixed slow-weight representations during training and lack mechanisms for rapid adaptation within an episode. In contrast, biological neura…