3 citations · 7 across the 7 of their papers we have counts for
10 papers · 1 filter
Lexical Knowledge Internalization for Neural Dialog Generation
Zhiyong Wu, Wei Bi, Xiang Li +2
We propose knowledge internalization (KI), which aims to complement the lexical knowledge into neural dialog models. Instead of further conditioning the knowledge-grounded dialog (…
A Model-Agnostic Data Manipulation Method for Persona-based Dialogue Generation
Yu Cao, Wei Bi, Meng Fang +2
Towards building intelligent dialogue agents, there has been a growing interest in introducing explicit personas in generation models. However, with limited persona-based dialogue…
Event Transition Planning for Open-ended Text Generation
Qintong Li, Piji Li, Wei Bi +3
Open-ended text generation tasks, such as dialogue generation and story completion, require models to generate a coherent continuation given limited preceding context. The open-end…
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…
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…
Pretrained Language Models for Dialogue Generation with Multiple Input Sources
Yu Cao, Wei Bi, Meng Fang +1
Large-scale pretrained language models have achieved outstanding performance on natural language understanding tasks. However, it is still under investigating how to apply them to…