no code implementations • NLP4ConvAI (ACL) 2022 • Tong Zhang, Yong liu, Boyang Li, Peixiang Zhong, Chen Zhang, Hao Wang, Chunyan Miao
Conversational Recommendation Systems recommend items through language based interactions with users. In order to generate naturalistic conversations and effectively utilize knowledge graphs (KGs) containing background information, we propose a novel Bag-of-Entities loss, which encourages the generated utterances to mention concepts related to the item being recommended, such as the genre or director of a movie.
no code implementations • 18 May 2021 • Tong Zhang, Yong liu, Peixiang Zhong, Chen Zhang, Hao Wang, Chunyan Miao
The chit-chat-based conversational recommendation systems (CRS) provide item recommendations to users through natural language interactions.
1 code implementation • 15 Dec 2020 • Peixiang Zhong, Yong liu, Hao Wang, Chunyan Miao
We study the problem of imposing conversational goals/keywords on open-domain conversational agents, where the agent is required to lead the conversation to a target keyword smoothly and fast.
no code implementations • 15 Dec 2020 • Peixiang Zhong, Di Wang, Pengfei Li, Chen Zhang, Hao Wang, Chunyan Miao
Experimental results on two large-scale datasets support our hypothesis and show that our model can produce more accurate and commonsense-aware emotional responses and achieve better human ratings than state-of-the-art models that only specialize in one aspect.
1 code implementation • EMNLP 2020 • Peixiang Zhong, Chen Zhang, Hao Wang, Yong liu, Chunyan Miao
To this end, we propose a new task towards persona-based empathetic conversations and present the first empirical study on the impact of persona on empathetic responding.
1 code implementation • IJCNLP 2019 • Peixiang Zhong, Di Wang, Chunyan Miao
Messages in human conversations inherently convey emotions.
Ranked #8 on Emotion Recognition in Conversation on EC
2 code implementations • 18 Jul 2019 • Peixiang Zhong, Di Wang, Chunyan Miao
Finally, investigations on the neuronal activities reveal important brain regions and inter-channel relations for EEG-based emotion recognition.
Ranked #1 on EEG Emotion Recognition on SEED-IV
1 code implementation • SEMEVAL 2019 • Peixiang Zhong, Chunyan Miao
In this paper we present our model on the task of emotion detection in textual conversations in SemEval-2019.
1 code implementation • 17 Nov 2018 • Peixiang Zhong, Di Wang, Chunyan Miao
Affect conveys important implicit information in human communication.