63 citations · 69 across the 8 of their papers we have counts for
8 papers
A Theory of General Difference in Continuous and Discrete Domain
Linmi Tao, Ruiyang Liu, Donglai Tao +4
Though a core element of the digital age, numerical difference algorithms struggle with noise susceptibility. This stems from a key disconnect between the infinitesimal quantities…
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…
Automatic Context Pattern Generation for Entity Set Expansion
Yinghui Li, Shulin Huang, Xinwei Zhang +6
Entity Set Expansion (ESE) is a valuable task that aims to find entities of the target semantic class described by given seed entities. Various Natural Language Processing (NLP) an…
The Past Mistake is the Future Wisdom: Error-driven Contrastive Probability Optimization for Chinese Spell Checking
Yinghui Li, Qingyu Zhou, Yangning Li +7
Chinese Spell Checking (CSC) aims to detect and correct Chinese spelling errors, which are mainly caused by the phonological or visual similarity. Recently, pre-trained language mo…
Mutltimodal AI Companion for Interactive Fairytale Co-creation
Ruiyang Liu, Predrag K. Nikolic
AI fairy tale companions play an important role in early childhood education as an augmentation for parents' efforts to close the participation gap and boost kids' mental and langu…
Are we ready for a new paradigm shift? A Survey on Visual Deep MLP
Ruiyang Liu, Yinghui Li, Linmi Tao +2
Recently, the proposed deep MLP models have stirred up a lot of interest in the vision community. Historically, the availability of larger datasets combined with increased computin…
Towards All-around Knowledge Transferring: Learning From Task-irrelevant Labels
Yinghui Li, Ruiyang Liu, ZiHao Zhang +4
Deep neural models have hitherto achieved significant performances on numerous classification tasks, but meanwhile require sufficient manually annotated data. Since it is extremely…
SofGAN: A Portrait Image Generator with Dynamic Styling
Anpei Chen, Ruiyang Liu, Ling Xie +3
Recently, Generative Adversarial Networks (GANs)} have been widely used for portrait image generation. However, in the latent space learned by GANs, different attributes, such as p…