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Found 4 papers, 1 papers with code
Re-embedding Difficult Samples via Mutual Information Constrained Semantically Oversampling for Imbalanced Text Classification
Difficult samples of the minority class in imbalanced text classification are usually hard to be classified as they are embedded into an overlapping semantic region with the majority class.
Relative Counterfactual Contrastive Learning for Mitigating Pretrained Stance Bias in Stance Detection
Then, based on masked language model prediction, we present a target-aware relative stance sample generation method for obtaining relative bias.
Function-words Enhanced Attention Networks for Few-Shot Inverse Relation Classification
The relation classification is to identify semantic relations between two entities in a given text.
Learning Disentangled Semantic Representations for Zero-Shot Cross-Lingual Transfer in Multilingual Machine Reading Comprehension
To explicitly transfer only semantic knowledge to the target language, we propose two groups of losses tailored for semantic and syntactic encoding and disentanglement.
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