9 citations · 25 across the 8 of their papers we have counts for
9 papers
Emage: Non-Autoregressive Text-to-Image Generation
Zhangyin Feng, Runyi Hu, Liangxin Liu +7
Autoregressive and diffusion models drive the recent breakthroughs on text-to-image generation. Despite their huge success of generating high-realistic images, a common shortcoming…
Chunk, Align, Select: A Simple Long-sequence Processing Method for Transformers
Jiawen Xie, Pengyu Cheng, Xiao Liang +2
Although dominant in natural language processing, transformer-based models remain challenged by the task of long-sequence processing, because the computational cost of self-attenti…
SkillNet-X: A Multilingual Multitask Model with Sparsely Activated Skills
Zhangyin Feng, Yong Dai, Fan Zhang +6
Traditional multitask learning methods basically can only exploit common knowledge in task- or language-wise, which lose either cross-language or cross-task knowledge. This paper p…
Effidit: Your AI Writing Assistant
Shuming Shi, Enbo Zhao, Duyu Tang +10
In this technical report, we introduce Effidit (Efficient and Intelligent Editing), a digital writing assistant that facilitates users to write higher-quality text more efficiently…
One Model, Multiple Modalities: A Sparsely Activated Approach for Text, Sound, Image, Video and Code
Yong Dai, Duyu Tang, Liangxin Liu +7
People perceive the world with multiple senses (e.g., through hearing sounds, reading words and seeing objects). However, most existing AI systems only process an individual modali…
Pretraining Chinese BERT for Detecting Word Insertion and Deletion Errors
Cong Zhou, Yong Dai, Duyu Tang +4
Chinese BERT models achieve remarkable progress in dealing with grammatical errors of word substitution. However, they fail to handle word insertion and deletion because BERT assum…
"Is Whole Word Masking Always Better for Chinese BERT?": Probing on Chinese Grammatical Error Correction
Yong Dai, Linyang Li, Cong Zhou +5
Whole word masking (WWM), which masks all subwords corresponding to a word at once, makes a better English BERT model. For the Chinese language, however, there is no subword becaus…
MarkBERT: Marking Word Boundaries Improves Chinese BERT
Linyang Li, Yong Dai, Duyu Tang +3
We present a Chinese BERT model dubbed MarkBERT that uses word information in this work. Existing word-based BERT models regard words as basic units, however, due to the vocabulary…
SkillNet-NLU: A Sparsely Activated Model for General-Purpose Natural Language Understanding
Fan Zhang, Duyu Tang, Yong Dai +3
Prevailing deep models are single-purpose and overspecialize at individual tasks. However, when being extended to new tasks, they typically forget previously learned skills and lea…