Review for NeurIPS paper: Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect

Weaknesses: Despite its intriguing new perspective, the paper has some weaknesses that need to be further addressed. First, the paper lacks experimental comparisons to many other long-tail classification methods such as LDAM, balanced loss, BNN, even though they were mentioned in related work. Second, the use of multi-head strategy is not related to the claimed theoretical founding and it makes the judgement on the effectiveness of the theoretical framework more difficult. To the reviewer's point view, a fairer comparison would be just using K 1 just as other imbalanced classification framework. Third, the final form of the de-confounding training is very similar to previous works with the only difference being the hyperparameter gamma in equation 7. It is unclear to the reviewer whether the performance improvement comes from tuning the hyperparamter which is not directly inspired from the theoretical framework.