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Found 7 papers, 4 papers with code
Plot Writing From Pre-Trained Language Models
We propose generating story plots using off-the-shelf PLMs while maintaining the benefit of content planning to generate cohesive and contentful stories.
Seed Word Selection for Weakly-Supervised Text Classification with Unsupervised Error Estimation
We then train interim models with individual candidate seed words.
Bootstrapping Large-Scale Fine-Grained Contextual Advertising Classifier from Wikipedia
The widely used advertising content taxonomy (IAB taxonomy) consists of 23 coarse-grained categories and 355 fine-grained categories.
Learning Only from Relevant Keywords and Unlabeled Documents
We consider a document classification problem where document labels are absent but only relevant keywords of a target class and unlabeled documents are given.
Lukthung Classification Using Neural Networks on Lyrics and Audios
Lukthung, a distinctive and long-established type of Thai music, is one of the most popular music genres in Thailand and has a specific group of listeners.
Combining Lightly-Supervised Text Classification Models for Accurate Contextual Advertising
In this paper we propose a lightly-supervised framework to rapidly build text classifiers for contextual advertising.
