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Found 6 papers, 1 papers with code
An interpretability framework for Similar case matching
Subsequently, our framework aligns the corresponding sentences in two legal cases to provide evidence of similarity.
A BERT-based Unsupervised Grammatical Error Correction Framework
Grammatical error correction (GEC) is a challenging task of natural language processing techniques.
Model and Evaluation: Towards Fairness in Multilingual Text Classification
The multilingual text representation module uses a multilingual pre-trained language model to represent the text, the language fusion module makes the semantic spaces of different languages tend to be consistent through contrastive learning, and the text debiasing module uses contrastive learning to make the model unable to identify sensitive attributes' information.
An Effective Deployment of Contrastive Learning in Multi-label Text Classification
We explore the effectiveness of contrastive learning for multi-label text classification tasks by the employment of these novel losses and provide a set of baseline models for deploying contrastive learning techniques on specific tasks.
A Chinese Spelling Check Framework Based on Reverse Contrastive Learning
Inspired by contrastive learning, we present a novel framework for Chinese spelling checking, which consists of three modules: language representation, spelling check and reverse contrastive learning.
CL-XABSA: Contrastive Learning for Cross-lingual Aspect-based Sentiment Analysis
In the distillation XABSA task, we further explore the comparative effectiveness of different data (source dataset, translated dataset, and code-switched dataset).
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
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