Although large language models (LLMs) have the potential to transform biomedical research, their ability to reason accurately across complex, data-rich domains remains unproven. To address this ...

As the world’s largest companies pour hundreds of billions of dollars into large language models, San Francisco-based Logical ...

The Kennedy College of Science, Richard A. Miner School of Computer & Information Sciences, invites you to attend a doctoral dissertation proposal defense by Nidhi Vakil, titled: "Foundations for ...

Abstract: Graph Neural Networks (GNNs) effectively model long-range dependencies by capturing high-order relationships in user-item graphs, emerging as a mainstream paradigm for building personalized ...

This project focuses on building a Knowledge Graph-Based Recommender System to enhance user-item interaction predictions. The system utilizes structured knowledge to improve recommendation accuracy, ...

Abstract: Graph Neural Networks (GNNs) have emerged as powerful tools in recommender systems, enabling the modeling of complex user-item interactions by leveraging graph-structured representations.

Machine learning and neural nets can be pretty handy, and people continue to push the envelope of what they can do both in high end server farms as well as slower systems. At the extreme end of the ...

1 Department of Computer Science and Engineering, Kishoreganj University, Kishoreganj, Bangladesh. 2 Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh. 3 ...