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References (23)

[1]
Consistent Explainers or Unreliable Narrators? Understanding LLM-generated Group Recommendations
2025Cedric Waterschoot, N. Tintarev et al.
[2]
Hierarchical Intent-guided Optimization with Pluggable LLM-Driven Semantics for Session-based Recommendation
2025Jinpeng Chen, Jianxiang He et al.
[3]
Retrieval Augmented Generation with Collaborative Filtering for Personalized Text Generation
2025Teng Shi, Jun Xu et al.
[4]
Counterfactual Language Reasoning for Explainable Recommendation Systems
2025Guanrong Li, Haolin Yang et al.
[5]
ARTS: A General and Efficient Multi-Task Self-Prompt Framework for Explainable Sequential Recommendation
2025Zunlong Liu, Yang Xu et al.
[6]
Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation
2025Shijie Wang, Wenqi Fan et al.
[7]
The Llama 3 Herd of Models
2024Abhimanyu Dubey, Abhinav Jauhri et al.
[8]
Retrieval-Augmented Conversational Recommendation with Prompt-based Semi-Structured Natural Language State Tracking
2024Sara Kemper, Justin Cui et al.
[9]
A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models
2024Wenqi Fan, Yujuan Ding et al.
[10]
Multimodal Contrastive Transformer for Explainable Recommendation
2024Zhuang Liu, Yunpu Ma et al.
[11]
Fine-Tuning Large Language Model Based Explainable Recommendation with Explainable Quality Reward
2024Mengyuan Yang, Mengying Zhu et al.
[12]
Unlocking the Potential of Large Language Models for Explainable Recommendations
2023Yucong Luo, Mingyue Cheng et al.
[13]
Triple Dual Learning for Opinion-based Explainable Recommendation
2023Yuting Zhang, Ying Sun et al.
[14]
RecExplainer: Aligning Large Language Models for Recommendation Model Interpretability
2023Yuxuan Lei, Jianxun Lian et al.
[15]
Personalized Prompt Learning for Explainable Recommendation
2022Lei Li, Yongfeng Zhang et al.
[16]
Quality Metrics in Recommender Systems: Do We Calculate Metrics Consistently?
2021Yan-Martin Tamm, Rinchin Damdinov et al.
[17]
Generate Neural Template Explanations for Recommendation
2020Lei Li, Yongfeng Zhang et al.
[18]
Relational Graph Attention Network for Aspect-based Sentiment Analysis
2020Kai Wang, Weizhou Shen et al.
[19]
Towards Controllable Explanation Generation for Recommender Systems via Neural Template
2020Lei Li, L. Chen et al.
[20]
KB4Rec: A Data Set for Linking Knowledge Bases with Recommender Systems
2018Wayne Xin Zhao, Gaole He et al.

Showing 20 of 23 references

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