1 citations · 3 across the 7 of their papers we have counts for
8 papers
Lexical Complexity Controlled Sentence Generation
Jinran Nie, Liner Yang, Yun Chen +3
Text generation rarely considers the control of lexical complexity, which limits its more comprehensive practical application. We introduce a novel task of lexical complexity contr…
COMPILING: A Benchmark Dataset for Chinese Complexity Controllable Definition Generation
Jiaxin Yuan, Cunliang Kong, Chenhui Xie +2
The definition generation task aims to generate a word's definition within a specific context automatically. However, owing to the lack of datasets for different complexities, the…
LitMind Dictionary: An Open-Source Online Dictionary
Cunliang Kong, Xuezhi Fang, Liner Yang +2
Dictionaries can help language learners to learn vocabulary by providing definitions of words. Since traditional dictionaries present word senses as discrete items in predefined in…
BLCU-ICALL at SemEval-2022 Task 1: Cross-Attention Multitasking Framework for Definition Modeling
Cunliang Kong, Yujie Wang, Ruining Chong +4
This paper describes the BLCU-ICALL system used in the SemEval-2022 Task 1 Comparing Dictionaries and Word Embeddings, the Definition Modeling subtrack, achieving 1st on Italian, 2…
Multitasking Framework for Unsupervised Simple Definition Generation
Cunliang Kong, Yun Chen, Hengyuan Zhang +2
The definition generation task can help language learners by providing explanations for unfamiliar words. This task has attracted much attention in recent years. We propose a novel…
Few-Shot Domain Adaptation for Grammatical Error Correction via Meta-Learning
Shengsheng Zhang, Yaping Huang, Yun Chen +3
Most existing Grammatical Error Correction (GEC) methods based on sequence-to-sequence mainly focus on how to generate more pseudo data to obtain better performance. Few work addre…