Adaptive Ranking-based Sample Selection for Weakly Supervised Class-imbalanced Text Classification

2 code implementations • 6 Oct 2022 • Linxin Song, Jieyu Zhang, Tianxiang Yang, Masayuki Goto

To obtain a large amount of training labels inexpensively, researchers have recently adopted the weak supervision (WS) paradigm, which leverages labeling rules to synthesize training labels rather than using individual annotations to achieve competitive results for natural language processing (NLP) tasks.

text-classification Text Classification