18 citations · 64 across the 20 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
cs.CL2021★ 1 cited
Data Augmentation for Text Generation Without Any Augmented Data
Wei Bi, Huayang Li, Jiacheng Huang
Data augmentation is an effective way to improve the performance of many neural text generation models. However, current data augmentation methods need to define or choose proper d…
cs.CL2021
Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks
Zhiliang Tian, Wei Bi, Zihan Zhang +3
Personalized conversation models (PCMs) generate responses according to speaker preferences. Existing personalized conversation tasks typically require models to extract speaker pr…
cs.CL2021
REAM: An Enhancement Approach to Reference-based Evaluation Metrics for Open-domain Dialog Generation
Jun Gao, Wei Bi, Ruifeng Xu +1
The lack of reliable automatic evaluation metrics is a major impediment to the development of open-domain dialogue systems. Various reference-based metrics have been proposed to ca…