RecWizard: A Toolkit for Conversational Recommendation with Modular, Portable Models and Interactive User Interface
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Abstract (arXiv)
We present a new Python toolkit called RecWizard for Conversational Recommender Systems (CRS). RecWizard offers support for development of models and interactive user interface, drawing from the best practices of the Huggingface ecosystems. CRS with RecWizard are modular, portable, interactive and Large Language Models (LLMs)-friendly, to streamline the learning process and reduce the additional effort for CRS research. For more comprehensive information about RecWizard, please check our GitHub https://github.com/McAuley-Lab/RecWizard.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 15 references that are in the map. First posted on arXiv 23 Feb 2024.
Builds on
8 of 15 references.
References · 8
- 2018Towards Deep Conversational Recommendationscited by 174
- 2017ParlAI: A Dialog Research Software Platformcited by 139
- 2020RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithmscited by 137
- 2022Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learningcited by 85
- 2023Leveraging Large Language Models in Conversational Recommender Systemscited by 63
- 2022RecBole 2.0: Towards a More Up-to-Date Recommendation Librarycited by 39
- 2021CRSLab: An Open-Source Toolkit for Building Conversational Recommender Systemcited by 34
- 2022FORCE: A Framework of Rule-Based Conversational Recommender Systemcited by 1
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Citing papers per year: 2025: 1.
1 paper.