CRSLab: An Open-Source Toolkit for Building Conversational Recommender System

Kun Zhou, Xiaolei Wang, Yuanhang Zhou, Chenzhan Shang, Yuan Cheng, Wayne Xin Zhao, Yaliang Li, Ji-Rong Wen


Abstract
In recent years, conversational recommender systems (CRSs) have drawn a wide attention in the research community, which focus on providing high-quality recommendations to users via natural language conversations. However, due to diverse scenarios and data formats, existing studies on CRSs lack unified and standardized implementation or comparison. To tackle this challenge, we release an open-source toolkit CRSLab, which provides a unified and extensible framework with highly-decoupled modules to develop CRSs. Based on this framework, we collect 6 commonly used human-annotated CRS datasets and implement 19 models that include advanced techniques such as graph neural networks and pre-training models. Besides, our toolkit provides a series of automatic evaluation protocols and a human-machine interaction interface to evaluate and compare different CRS methods. The project and documents are released at https://github.com/RUCAIBox/CRSLab.
Anthology ID:
2021.acl-demo.22
Volume:
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
185–193
Language:
URL:
https://aclanthology.org/2021.acl-demo.22
DOI:
10.18653/v1/2021.acl-demo.22
Bibkey:
Cite (ACL):
Kun Zhou, Xiaolei Wang, Yuanhang Zhou, Chenzhan Shang, Yuan Cheng, Wayne Xin Zhao, Yaliang Li, and Ji-Rong Wen. 2021. CRSLab: An Open-Source Toolkit for Building Conversational Recommender System. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations, pages 185–193, Online. Association for Computational Linguistics.
Cite (Informal):
CRSLab: An Open-Source Toolkit for Building Conversational Recommender System (Zhou et al., ACL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.acl-demo.22.pdf
Video:
 https://aclanthology.org/2021.acl-demo.22.mp4
Code
 RUCAIBox/CRSLab
Data
DuRecDialReDialTG-ReDial