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Found 4 papers, 1 papers with code
TACIT: A Target-Agnostic Feature Disentanglement Framework for Cross-Domain Text Classification
However, these methods rely on unlabeled samples provided by the target domains, which renders the model ineffective when the target domain is agnostic.
A Survey on Fairness in Large Language Models
Large Language Models (LLMs) have shown powerful performance and development prospects and are widely deployed in the real world.
Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases
Meanwhile, experimental results on the GLUE benchmark show that CCPA retains the language modeling capability of PLMs.
Automatic Counterfactual Augmentation for Robust Text Classification Based on Word-Group Search
Despite large-scale pre-trained language models have achieved striking results for text classificaion, recent work has raised concerns about the challenge of shortcut learning.
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