Reviews: Self-Supervised Generalisation with Meta Auxiliary Learning

Though I think this paper proposed a very interesting approach to automating the design of auxiliary tasks. I am disappointed by its practical value on the image classification tasks evaluated. According to Table 1, the method outperformed the standard single-task learning baseline by a very small margin (less than 1%) on all seven datasets. Why didn't we see larger performance gains using the proposed approach? I'd hope to hear the authors' hypothesis.