rephrase "The tubular-wise learning framework is application-worthy for re-weighting methods in robust learning with noisy data. To begin with, we compare our method with previous adaptive re-weighting methods which are all based on the meta-learning framework. Then, ablation studies are conducted with the components of our framework to verify the effect of our design. Lastly, further experiments are performed to discuss the relationship between the amount of meta-data and robust learning."