20 citations · 78 across the 16 of their papers we have counts for
4 papers · 1 filter
GENIUS: Sketch-based Language Model Pre-training via Extreme and Selective Masking for Text Generation and Augmentation
Biyang Guo, Yeyun Gong, Yelong Shen +4
We introduce GENIUS: a conditional text generation model using sketches as input, which can fill in the missing contexts for a given sketch (key information consisting of textual s…
IDEA: Interactive DoublE Attentions from Label Embedding for Text Classification
Ziyuan Wang, Hailiang Huang, Songqiao Han
Current text classification methods typically encode the text merely into embedding before a naive or complicated classifier, which ignores the suggestive information contained in…
Selective Text Augmentation with Word Roles for Low-Resource Text Classification
Biyang Guo, Songqiao Han, Hailiang Huang
Data augmentation techniques are widely used in text classification tasks to improve the performance of classifiers, especially in low-resource scenarios. Most previous methods con…
ADBench: Anomaly Detection Benchmark
Songqiao Han, Xiyang Hu, Hailiang Huang +2
Given a long list of anomaly detection algorithms developed in the last few decades, how do they perform with regard to (i) varying levels of supervision, (ii) different types of a…