18 citations · 86 across the 9 of their papers we have counts for
10 papers · 1 filter
Parameter-Efficient Tuning on Layer Normalization for Pre-trained Language Models
Wang Qi, Yu-Ping Ruan, Yuan Zuo +1
Conventional fine-tuning encounters increasing difficulties given the size of current Pre-trained Language Models, which makes parameter-efficient tuning become the focal point of…
SemEval-2021 Task 4: Reading Comprehension of Abstract Meaning
Boyuan Zheng, Xiaoyu Yang, Yu-Ping Ruan +4
This paper introduces the SemEval-2021 shared task 4: Reading Comprehension of Abstract Meaning (ReCAM). This shared task is designed to help evaluate the ability of machines in re…
Emotion-Regularized Conditional Variational Autoencoder for Emotional Response Generation
Yu-Ping Ruan, Zhen-Hua Ling
This paper presents an emotion-regularized conditional variational autoencoder (Emo-CVAE) model for generating emotional conversation responses. In conventional CVAE-based emotiona…
Pre-Trained and Attention-Based Neural Networks for Building Noetic Task-Oriented Dialogue Systems
Jia-Chen Gu, Tianda Li, Quan Liu +3
The NOESIS II challenge, as the Track 2 of the 8th Dialogue System Technology Challenges (DSTC 8), is the extension of DSTC 7. This track incorporates new elements that are vital f…
Fine-Tuning BERT for Schema-Guided Zero-Shot Dialogue State Tracking
Yu-Ping Ruan, Zhen-Hua Ling, Jia-Chen Gu +1
We present our work on Track 4 in the Dialogue System Technology Challenges 8 (DSTC8). The DSTC8-Track 4 aims to perform dialogue state tracking (DST) under the zero-shot settings,…
Condition-Transforming Variational AutoEncoder for Conversation Response Generation
Yu-Ping Ruan, Zhen-Hua Ling, Quan Liu +2
This paper proposes a new model, called condition-transforming variational autoencoder (CTVAE), to improve the performance of conversation response generation using conditional var…