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Found 6 papers, 2 papers with code
Contrastive Learning Subspace for Text Clustering
Contrastive learning has been frequently investigated to learn effective representations for text clustering tasks.
G-SPEED: General SParse Efficient Editing MoDel
Large Language Models~(LLMs) have demonstrated incredible capabilities in understanding, generating, and manipulating languages.
A Pairing Enhancement Approach for Aspect Sentiment Triplet Extraction
Aspect Sentiment Triplet Extraction (ASTE) aims to extract the triplet of an aspect term, an opinion term, and their corresponding sentiment polarity from the review texts.
Friend-training: Learning from Models of Different but Related Tasks
Current self-training methods such as standard self-training, co-training, tri-training, and others often focus on improving model performance on a single task, utilizing differences in input features, model architectures, and training processes.
Towards Accurate and Consistent Evaluation: A Dataset for Distantly-Supervised Relation Extraction
The experimental results show that the ranking lists of the comparison systems on the DS-labelled test data and human-annotated test data are different.
Emotion Detection with Neural Personal Discrimination
Accordingly, we propose a Neural Personal Discrimination (NPD) approach to address above challenges by determining personal attributes from posts, and connecting relevant posts with similar attributes to jointly learn their emotions.
