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Large-scale pretrained language models such as T5 and BERT have demonstrated strong capabilities for generating struc...
While Large Language Models (LLMs) excel at many tasks, they frequently struggle with complex reasoning that requires...
Medical image encoders from different groups are increasingly treated as interchangeable, on the assumption that scal...
We propose a novel framework for computing rigorous bounds on the probability that a large language model (LLM) gener...
We consider a task planning scenario in which robots sharing a persistent environment are assigned tasks one at a tim...
AI artifacts move through a multi-platform supply chain, spanning datasets and models on Hugging Face and application...
RGB-D semantic segmentation has achieved remarkable progress, yet most models assume that RGB and depth are always av...
This study empirically analyzed generative AI as an emerging discovery pathway to academic library resources. Utilizi...
Closing the gap between benchmark performance and reliable real-world operation remains a central challenge for Visio...
Generative AI can produce book-length works of fiction at near-zero cost. These books are often dismissed as low-qual...
Natural-language autoencoders score explanations of hidden activations by reconstruction: an explanation is deemed fa...
Clinical biomarker workflows in translational research settings often rely on spreadsheet-driven tracking, manual qua...