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Found 8 papers, 2 papers with code
A Survey on Multilingual Large Language Models: Corpora, Alignment, and Bias
Based on the foundation of Large Language Models (LLMs), Multilingual Large Language Models (MLLMs) have been developed to address the challenges of multilingual natural language processing tasks, hoping to achieve knowledge transfer from high-resource to low-resource languages.
Using Whole Slide Image Representations from Self-Supervised Contrastive Learning for Melanoma Concordance Regression
We also investigated the performance of using the predicted concordance rate as a malignancy classifier, and achieved a precision and recall of 0. 85 +/- 0. 05 and 0. 61 +/- 0. 06, respectively, on the test set.
Robust No-Regret Learning in Min-Max Stackelberg Games
In this paper, we investigate the behavior of no-regret learning in min-max games with dependent strategy sets, where the strategy of the first player constrains the behavior of the second.
MoDL-QSM: Model-based Deep Learning for Quantitative Susceptibility Mapping
However, there exists a mismatch between the observed phase and the theoretical forward phase estimated by the susceptibility label.
Learning unbiased zero-shot semantic segmentation networks via transductive transfer
Our method assumes that both the source images with full pixel-level labels and unlabeled target images are available during training.
