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Found 2 papers, 1 papers with code
Language Grounded QFormer for Efficient Vision Language Understanding
Large-scale pretraining and instruction tuning have been successful for training general-purpose language models with broad competencies.
Avoiding spurious correlations via logit correction
Empirical studies suggest that machine learning models trained with empirical risk minimization (ERM) often rely on attributes that may be spuriously correlated with the class labels.
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