Papers by Chenzhan Shang

1 papers
CRSLab: An Open-Source Toolkit for Building Conversational Recommender System (2021.acl-demo)

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Challenge: Existing studies on conversational recommender systems lack a unified and standardized implementation or comparison.
Approach: They propose to use a unified framework and highly-decoupled modules to develop CRSs.
Outcome: The proposed framework collects 6 commonly used human-annotated CRS datasets and implements 19 models that include advanced techniques such as graph neural networks and pre-training models.

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