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Found 3 papers, 1 papers with code
Delving into Identify-Emphasize Paradigm for Combating Unknown Bias
For challenge B, we point out that the gradient contribution statistics can be a reliable indicator to inspect whether the optimization is dominated by bias-aligned samples.
Controller-Guided Partial Label Consistency Regularization with Unlabeled Data
Partial label learning (PLL) learns from training examples each associated with multiple candidate labels, among which only one is valid.
Combating Unknown Bias with Effective Bias-Conflicting Scoring and Gradient Alignment
For challenge B, we point out that the gradient contribution statistics can be a reliable indicator to inspect whether the optimization is dominated by bias-aligned samples.
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