2 citations · 4 across the 5 of their papers we have counts for
6 papers
Visually Grounded Commonsense Knowledge Acquisition
Yuan Yao, Tianyu Yu, Ao Zhang +8
Large-scale commonsense knowledge bases empower a broad range of AI applications, where the automatic extraction of commonsense knowledge (CKE) is a fundamental and challenging pro…
Linguistic Rules-Based Corpus Generation for Native Chinese Grammatical Error Correction
Shirong Ma, Yinghui Li, Rongyi Sun +9
Chinese Grammatical Error Correction (CGEC) is both a challenging NLP task and a common application in human daily life. Recently, many data-driven approaches are proposed for the…
Learning from the Dictionary: Heterogeneous Knowledge Guided Fine-tuning for Chinese Spell Checking
Yinghui Li, Shirong Ma, Qingyu Zhou +7
Chinese Spell Checking (CSC) aims to detect and correct Chinese spelling errors. Recent researches start from the pretrained knowledge of language models and take multimodal inform…
Global Mixup: Eliminating Ambiguity with Clustering
Xiangjin Xie, Yangning Li, Wang Chen +3
Data augmentation with \textbf{Mixup} has been proven an effective method to regularize the current deep neural networks. Mixup generates virtual samples and corresponding labels a…
ASR-GLUE: A New Multi-task Benchmark for ASR-Robust Natural Language Understanding
Lingyun Feng, Jianwei Yu, Deng Cai +3
Language understanding in speech-based systems have attracted much attention in recent years with the growing demand for voice interface applications. However, the robustness of na…
Coupling Distant Annotation and Adversarial Training for Cross-Domain Chinese Word Segmentation
Ning Ding, Dingkun Long, Guangwei Xu +4
Fully supervised neural approaches have achieved significant progress in the task of Chinese word segmentation (CWS). Nevertheless, the performance of supervised models tends to dr…