If you consider each label to be a node in the final layer of the network,  “pos_weight” will help in tacking the class imbalance in each node individually (check the formula in documentation 40). For example in a multi-label binary classification with 4 labels, it will help in assigning weights to the positive class for each label individually. The weighting system mentioned here will help in assigning importance to each of the individual losses calculated for each of the 4 labels. This will not necessarily tackle the class imbalance problem, but I think should scale the gradients from a node.