CRSLab is an open-source toolkit for building Conversational Recommender System (CRS).

Conversational Recommender System (CRS) paper list. 对话推荐系统论文列表

Must-read Papers for Recommender Systems (RS)

Code for paper: Towards Conversational Search and Recommendation: System Ask, User Respond

the Pytorch implementation for our EMNLP 2021 paper "Learning Neural Templates for Recommender Dialogue System"

[TNNLS] Knowledge Graphs and Pre-trained Language Models enhanced Representation Learning for Conversational Recommender Systems

[KDD23] Official PyTorch implementation for "Improving Conversational Recommendation Systems via Counterfactual Data Simulation".

Official PyTorch implementation for "Multi-grained Hypergraph Interest Modeling for Conversational Recommendation".

Neureca: a chatbot framework for Conversational Recommender Systems

[ICDM] Official Implementation of Reasoning over User Preferences: Knowledge Graph‑Augmented LLMs for Explainable Conversational Recommendations

A Comparative Study on Joint Intent Detection and Slot Filling models based on MultiWOZ dataset