Contrastive learning models for sentence representations
Sentence representation learning is a crucial task in natural language processing, as the
quality of learned representations directly influences downstream tasks, such as sentence …
quality of learned representations directly influences downstream tasks, such as sentence …
[HTML][HTML] Contrastive sentence representation learning with adaptive false negative cancellation
Contrastive sentence representation learning has made great progress thanks to a range of
text augmentation strategies and hard negative sampling techniques. However, most studies …
text augmentation strategies and hard negative sampling techniques. However, most studies …
Cpl: Counterfactual prompt learning for vision and language models
Prompt tuning is a new few-shot transfer learning technique that only tunes the learnable
prompt for pre-trained vision and language models such as CLIP. However, existing prompt …
prompt for pre-trained vision and language models such as CLIP. However, existing prompt …
A multi-level supervised contrastive learning framework for low-resource natural language inference
Natural Language Inference (NLI) is a growingly essential task in natural language
understanding, which requires inferring the relationship between the sentence pairs …
understanding, which requires inferring the relationship between the sentence pairs …
Facilitating contrastive learning of discourse relational senses by exploiting the hierarchy of sense relations
Implicit discourse relation recognition is a challenging task that involves identifying the
sense or senses that hold between two adjacent spans of text, in the absence of an explicit …
sense or senses that hold between two adjacent spans of text, in the absence of an explicit …
A survey of methods for addressing class imbalance in deep-learning based natural language processing
Many natural language processing (NLP) tasks are naturally imbalanced, as some target
categories occur much more frequently than others in the real world. In such scenarios …
categories occur much more frequently than others in the real world. In such scenarios …