10 citations · 11 across the 4 of their papers we have counts for
4 papers
Learning to Adapt to Low-Resource Paraphrase Generation
Zhigen Li, Yanmeng Wang, Rizhao Fan +3
Paraphrase generation is a longstanding NLP task and achieves great success with the aid of large corpora. However, transferring a paraphrasing model to another domain encounters t…
Knowledge Transfer-Driven Few-Shot Class-Incremental Learning
Ye Wang, Yaxiong Wang, Guoshuai Zhao +1
Few-shot class-incremental learning (FSCIL) aims to continually learn new classes using a few samples while not forgetting the old classes. The key of this task is effective knowle…
Advanced Conditional Variational Autoencoders (A-CVAE): Towards interpreting open-domain conversation generation via disentangling latent feature representation
Ye Wang, Jingbo Liao, Hong Yu +3
Currently end-to-end deep learning based open-domain dialogue systems remain black box models, making it easy to generate irrelevant contents with data-driven models. Specifically,…
Enhancing Dual-Encoders with Question and Answer Cross-Embeddings for Answer Retrieval
Yanmeng Wang, Jun Bai, Ye Wang +5
Dual-Encoders is a promising mechanism for answer retrieval in question answering (QA) systems. Currently most conventional Dual-Encoders learn the semantic representations of ques…