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Hi, thank you for your great work~ I have a few questions regarding my understanding of the paper:
1.According to Figure 1, I understand that auxiliary OOD data are also used during training, similar to outlier exposure, is that correct?
2.In the "Debiased Large Margin Learning Calibration" module, the schematic diagram does not illustrate the operation of pulling OOD categories. However, the text mentions "since we have already pulled OOD samples together in the joint LTR and outlier class learning in Eq. 2", does this mean there is an operation to pull the entire OOD category?
If so, considering that OOD data have diverse categories and their distribution is theoretically unknown, how can we ensure they cluster together in the feature space?
I would greatly appreciate it if you could provide some clarification.
The text was updated successfully, but these errors were encountered:
Hi, thank you for your great work~ I have a few questions regarding my understanding of the paper:
1.According to Figure 1, I understand that auxiliary OOD data are also used during training, similar to outlier exposure, is that correct?
2.In the "Debiased Large Margin Learning Calibration" module, the schematic diagram does not illustrate the operation of pulling OOD categories. However, the text mentions "since we have already pulled OOD samples together in the joint LTR and outlier class learning in Eq. 2", does this mean there is an operation to pull the entire OOD category?
If so, considering that OOD data have diverse categories and their distribution is theoretically unknown, how can we ensure they cluster together in the feature space?
I would greatly appreciate it if you could provide some clarification.
The text was updated successfully, but these errors were encountered: