4 citations · 8 across the 9 of their papers we have counts for
10 papers
Stylized Knowledge-Grounded Dialogue Generation via Disentangled Template Rewriting
Qingfeng Sun, Can Xu, Huang Hu +6
Current Knowledge-Grounded Dialogue Generation (KDG) models specialize in producing rational and factual responses. However, to establish long-term relationships with users, the KD…
FORCE: A Framework of Rule-Based Conversational Recommender System
Jun Quan, Ze Wei, Qiang Gan +11
The conversational recommender systems (CRSs) have received extensive attention in recent years. However, most of the existing works focus on various deep learning models, which ar…
PromDA: Prompt-based Data Augmentation for Low-Resource NLU Tasks
Yufei Wang, Can Xu, Qingfeng Sun +4
This paper focuses on the Data Augmentation for low-resource Natural Language Understanding (NLU) tasks. We propose Prompt-based D}ata Augmentation model (PromDA) which only trains…
TegTok: Augmenting Text Generation via Task-specific and Open-world Knowledge
Chao-Hong Tan, Jia-Chen Gu, Chongyang Tao +5
Generating natural and informative texts has been a long-standing problem in NLP. Much effort has been dedicated into incorporating pre-trained language models (PLMs) with various…
HeterMPC: A Heterogeneous Graph Neural Network for Response Generation in Multi-Party Conversations
Jia-Chen Gu, Chao-Hong Tan, Chongyang Tao +4
Recently, various response generation models for two-party conversations have achieved impressive improvements, but less effort has been paid to multi-party conversations (MPCs) wh…
ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification
Yucheng Zhou, Tao Shen, Xiubo Geng +2
Generating new events given context with correlated ones plays a crucial role in many event-centric reasoning tasks. Existing works either limit their scope to specific scenarios o…