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Found 5 papers, 1 papers with code
RADIN: Souping on a Budget
Model Soups, extending Stochastic Weights Averaging (SWA), combine models fine-tuned with different hyperparameters.
Prompt Performance Prediction for Image Generation
The ability to predict the performance of a query before results are returned has been a longstanding challenge in Information Retrieval (IR) systems.
Fine-tune your Classifier: Finding Correlations With Temperature
Temperature is a widely used hyperparameter in various tasks involving neural networks, such as classification or metric learning, whose choice can have a direct impact on the model performance.
What can we Learn by Predicting Accuracy?
The formula discovered on more than 260 datasets of embeddings has a Pearson's correlation of 0. 96 and a $r^2$ of 0. 93.
Learning an Adaptation Function to Assess Image Visual Similarities
As a consequence, such features are powerful to compare semantically related images but not really efficient to compare images visually similar but semantically unrelated.
