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Found 3 papers, 1 papers with code
Just Mix Once: Worst-group Generalization by Group Interpolation
Advances in deep learning theory have revealed how average generalization relies on superficial patterns in data.
PARS: Pseudo-Label Aware Robust Sample Selection for Learning with Noisy Labels
In this paper, we propose PARS: Pseudo-Label Aware Robust Sample Selection, a hybrid approach that combines the best from all three worlds in a joint-training framework to achieve robustness to noisy labels.
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
Predominantly, two formulations are used for sentence-pair tasks: bi-encoders and cross-encoders.
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