REsponsible & Accountable Learning (REAL)
@ University of California, Santa Cruz

1st LMNL challange selected leaderboard

We provide the participants, accuracy/F1-score for top 3 teams. Code link and reports of approved teams are given as well.
For CIFAR-10N sub-competitions, we attach the results on CIFAR-10N (aggre, rand1, worst). 
All reported accuracy (learning task) and F1-score (detection task) are the mean of 5 runs.


For participants, please contact us via {yangliu, jiahengwei, zwzhu, haocheng}
if you want to add your methods onto this competition leaderboard.
We are also maintaining a curated list of most recent papers & codes in learning with noisy labels here.