6 papers
Evidence of a Cognitive Shift in AI Education: How Students Are Rethinking Human Intelligence?
Islem Rekik
Perceptions of intelligence shape how learners evaluate and rely on artificial intelligence (AI) systems. Despite rapid advances in AI capabilities, the impact of sustained exposur…
Reservoir-Based Graph Convolutional Networks
Mayssa Soussia, Gita Ayu Salsabila, Mohamed Ali Mahjoub +1
Message passing is a core mechanism in Graph Neural Networks (GNNs), enabling the iterative update of node embeddings by aggregating information from neighboring nodes. Graph Convo…
HGNet: Scalable Foundation Model for Automated Knowledge Graph Generation from Scientific Literature
Devvrat Joshi, Islem Rekik
Automated knowledge graph (KG) construction is essential for navigating the rapidly expanding body of scientific literature. However, existing approaches struggle to recognize long…
Rethinking Graph Super-resolution: Dual Frameworks for Topological Fidelity
Pragya Singh, Islem Rekik
Graph super-resolution, the task of inferring high-resolution (HR) graphs from low-resolution (LR) counterparts, is an underexplored yet crucial research direction that circumvents…
DeltaGNN: Graph Neural Network with Information Flow Control
Kevin Mancini, Islem Rekik
Graph Neural Networks (GNNs) are popular deep learning models designed to process graph-structured data through recursive neighborhood aggregations in the message passing process.…
DuoGNN: Topology-aware Graph Neural Network with Homophily and Heterophily Interaction-Decoupling
K. Mancini, I. Rekik
Graph Neural Networks (GNNs) have proven effective in various medical imaging applications, such as automated disease diagnosis. However, due to the local neighborhood aggregation…