15 citations · 18 across the 4 of their papers we have counts for
4 papers · 1 filter
Prompting through Prototype: A Prototype-based Prompt Learning on Pretrained Vision-Language Models
Yue Zhang, Hongliang Fei, Dingcheng Li +2
Prompt learning is a new learning paradigm which reformulates downstream tasks as similar pretraining tasks on pretrained models by leveraging textual prompts. Recent works have de…
Learning to Selectively Learn for Weakly-supervised Paraphrase Generation
Kaize Ding, Dingcheng Li, Alexander Hanbo Li +4
Paraphrase generation is a longstanding NLP task that has diverse applications for downstream NLP tasks. However, the effectiveness of existing efforts predominantly relies on larg…
Be More with Less: Hypergraph Attention Networks for Inductive Text Classification
Kaize Ding, Jianling Wang, Jundong Li +2
Text classification is a critical research topic with broad applications in natural language processing. Recently, graph neural networks (GNNs) have received increasing attention i…
Meta-CoTGAN: A Meta Cooperative Training Paradigm for Improving Adversarial Text Generation
Haiyan Yin, Dingcheng Li, Xu Li +1
Training generative models that can generate high-quality text with sufficient diversity is an important open problem for Natural Language Generation (NLG) community. Recently, gen…