Abstract: Federated learning is an emerging machine learning paradigm that effectively alleviates the data silo problem by distributing the model training process to multiple data holders. However, ...
A new study finds that large language models (LLMs), used with straightforward prompting, perform poorly on routine ...
Abstract: Open-vocabulary multi-label classification aims to identify the labels for all significant objects of interest in the scene, including new objects unseen in the training set. Recent studies ...
Google's new Multi-Token Prediction drafters can make Gemma 4 run up to 3x faster on your own hardware—no cloud required, and ...
Molecular pathology has entered a transformative era under the influence of artificial intelligence (AI). The intersection of digital pathology, molecular ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results