The discussion reveals that selecting the right model may be less critical than previously thought, as various models can yield effective disentanglement representations. However, determining optimal hyperparameters remains a significant challenge, especially without access to ground truth labels. Even when trained under identical conditions, models can produce vastly different results, complicating the selection process further.
