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Found 4 papers, 2 papers with code
Few-shot Adaptation Works with UnpredicTable Data
Finetuning on the resulting dataset leads to improved FSL performance on Natural Language Processing (NLP) tasks, but not proportionally to dataset scale.
Training Language Models with Language Feedback
We learn from language feedback on model outputs using a three-step learning algorithm.
Instance-wise algorithm configuration with graph neural networks
We pose this task as a supervised learning problem: First, we compile a large dataset of the solver performance for various configurations and all provided MILP instances.
Semantic Segmentation of Histopathological Slides for the Classification of Cutaneous Lymphoma and Eczema
Second, using the segmentation map and the original image, we are able to predict if a patient has MF or Eczema.
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