Unraveling and Mitigating Retriever Inconsistencies in Retrieval-Augmented Large Language Models

findings of ACL

Mingda, Li and Xinyu, Li and Yifan, Chen and Wenfeng, Xuan and Wei-Nan, Zhang

Unraveling and Mitigating Retriever Inconsistencies in Retrieval-Augmented Large Language Models

findings of ACL

Mingda, Li and Xinyu, Li and Yifan, Chen and Wenfeng, Xuan and Wei-Nan, Zhang

Conversational Recommender System and Large Language Model Are Made for Each Other in E-commerce Pre-sales Dialogue

Findings of EMNLP

Liu, Yuanxing and Zhang, Wei-Nan and Chen, Yifan and Zhang, Yuchi and Bai, Haopeng and Feng, Fan and Cui, Hengbin and Li, Yongbin and Che, Wanxiang

Conversational Recommender System and Large Language Model Are Made for Each Other in E-commerce Pre-sales Dialogue

Findings of EMNLP

Liu, Yuanxing and Zhang, Wei-Nan and Chen, Yifan and Zhang, Yuchi and Bai, Haopeng and Feng, Fan and Cui, Hengbin and Li, Yongbin and Che, Wanxiang

U-NEED: A Fine-grained Dataset for User Needs-Centric E-commerce Conversational Recommendation

SIGIR

Liu, Yuanxing and Zhang, Weinan and Dong, Baohua and Fan, Yan and Wang, Hang and Feng, Fan and Chen, Yifan and Zhuang, Ziyu and Cui, Hengbin and Li, Yongbin and Che, Wanxiang

U-NEED: A Fine-grained Dataset for User Needs-Centric E-commerce Conversational Recommendation

SIGIR

Liu, Yuanxing and Zhang, Weinan and Dong, Baohua and Fan, Yan and Wang, Hang and Feng, Fan and Chen, Yifan and Zhuang, Ziyu and Cui, Hengbin and Li, Yongbin and Che, Wanxiang