Biologists have long puzzled over why organisms with similar numbers of protein-coding genes can differ so dramatically in ...
Ligand-based drug design combines AI and QSAR modeling to prioritize drug candidates, minimizing preclinical failures and ...
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AI Researchers Are Confronting the Gap Between Neural Network Power and True Generalization
In 2026, neural networks are achieving unprecedented capabilities across industries, yet large-scale tests reveal persistent struggles with generalization. Researchers are exploring adaptive ...
Abstract: Traffic flow forecasting task plays an essential role in intelligent transportation systems. Accurately capturing the intricate spatio-temporal dependencies in traffic network signals is the ...
In 2026, AI research is moving beyond raw scaling to focus on efficiency, adaptability, and operational robustness. Advances in architectures, benchmarks, and conferences reflect a growing emphasis on ...
Abstract: This paper focuses on representation learning for dynamic graphs with temporal interactions. A fundamental issue is that both the graph structure and the nodes own their own dynamics, and ...
Scientists have created a new way to map how brain cells connect by assigning each neuron a unique molecular “barcode.” Using ...
Atlassian Corp. today unveiled a sweeping set of artificial intelligence updates at its annual Team ’26 conference, headlined ...
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