Learning to Generate Product Reviews from Attributes

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Disentangled CVAEs with Contrastive Learning for Explainable Recommendation

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UCEpic: Unifying Aspect Planning and Lexical Constraints for Generating Explanations in Recommendation

Li, J., He, Z., Shang, J., & McAuley, J. (2023) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3580305.3599535 · Cited by 15 · see citing works

Uncertainty-Aware Explainable Recommendation with Large Language Models

Peng, Y., Chen, H., Lin, C.-S., Huang, G., Hu, J., Guo, H., Kong, B., Hu, S., Wu, X., & Wang, X. (2024) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn60899.2024.10651104 · Cited by 16 · see citing works

Neural Review Summarization Leveraging User and Product Information

Liu, H., & Wan, X. (2019) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3357384.3358161 · Cited by 14 · see citing works

Explainable Recommendation Using Review Text and a Knowledge Graph

Suzuki, T. J., Oyama, S., & Kurihara, M. (2019) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata47090.2019.9005590 · Cited by 14 · see citing works

Synthesizing Aspect-Driven Recommendation Explanations from Reviews

Le, T.-H., & Lauw, H. W. (2020) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2020/336 · Cited by 14 · see citing works

Chain-of-thought prompting empowered generative user modeling for personalized recommendation

Yang, F., Yue, Y., Li, G., Payne, T. R., & Man, K. L. (2024) · Neural Computing and Applications · doi:10.1007/s00521-024-10364-2 · Cited by 13 · see citing works

TWT: Table with Written Text for Controlled Data-to-Text Generation

Li, T., Fang, L., Lou, J., & Li, Z. (2021) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2021.findings-emnlp.107 · Cited by 12 · see citing works

Improving Controllable Text Generation with Position-Aware Weighted Decoding

Gu, Y., Feng, X., Ma, S., Wu, J., Gong, H., & Qin, B. (2022) · Findings of the Association for Computational Linguistics: ACL 2022 · doi:10.18653/v1/2022.findings-acl.272 · Cited by 12 · see citing works

A Comparative Analysis of Text-Based Explainable Recommender Systems

Ariza-Casabona, A., Boratto, L., & Salamó, M. (2024) · ACM Conference on Recommender Systems (RecSys) · doi:10.1145/3640457.3688069 · Cited by 12 · see citing works

Transformer Reasoning Network for Personalized Review Summarization

Xu, H., Liu, H., Jiao, P., & Wang, W. (2021) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3404835.3462854 · Cited by 11 · see citing works

Improving Explainable Recommendations by Deep Review-Based Explanations

Ouyang, S., & Lawlor, A. (2021) · IEEE Access · doi:10.1109/access.2021.3076146 · Cited by 11 · see citing works

Natural Language Processing for Recommender Systems

Shalom, O. S., Roitman, H., & Kouki, P. (2021) · Springer eBooks · doi:10.1007/978-1-0716-2197-4_12 · Cited by 11 · see citing works

The Problem of Coherence in Natural Language Explanations of Recommendations

Raczyński, J., Lango, M., & Stefanowski, J. (2023) · Frontiers in artificial intelligence and applications · doi:10.3233/faia230482 · Cited by 10 · see citing works

Aspect-guided Syntax Graph Learning for Explainable Recommendation

Hu, Y., Liu, Y., Miao, C., Lin, G., & Miao, Y. (2022) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2022.3221847 · Cited by 10 · see citing works

Hierarchical template transformer for fine-grained sentiment controllable generation

Li, Y., Wang, J., Yu, L.-C., & Zhang, X. (2022) · Information Processing & Management · doi:10.1016/j.ipm.2022.103048 · Cited by 10 · see citing works

Rating-boosted abstractive review summarization with neural personalized generation

Xu, H., Liu, H., Zhang, W., Jiao, P., & Wang, W. (2021) · Knowledge-Based Systems · doi:10.1016/j.knosys.2021.106858 · Cited by 10 · see citing works

DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-ExpertsPreprint

Liu, A., Sap, M., Lu, X., Swayamdipta, S., Bhagavatula, C., Smith, N. A., & Choi, Y. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.03023 · Cited by 10 · see citing works

Comparative analysis of methodologies and approaches in recommender systems utilizing large language models

Elmoghazy, S. S., Shouman, M. A., Elminir, H. K., & Selim, G. E. I. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11189-8 · Cited by 11 · see citing works

J3R: Joint Multi-task Learning of Ratings and Review Summaries for Explainable Recommendation

Avinesh, P. V. S., Ren, Y., Meyer, C. M., Chan, J., Bao, Z., & Sanderson, M. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-46133-1_21 · Cited by 9 · see citing works

Applications and challenges of SA in real-life scenarios

Kanojia, D., & Joshi, A. (2023) · Elsevier eBooks · doi:10.1016/b978-0-32-390535-0.00008-2 · Cited by 9 · see citing works

Predictive Prompts with Joint Training of Large Language Models for Explainable Recommendation

Lin, C.-S., Tsai, C.-N., Su, S.-T., Jwo, J., Lee, C., & Wang, X. E. (2023) · Mathematics · doi:10.3390/math11204230 · Cited by 9 · see citing works

A Product Recommendation System Based on User Complaint Analysis Using Product Reviews

Yoshikawa, T., Wang, Y., & Kawai, Y. (2019) · IEEE Global Conference on Consumer Electronics (GCCE) · doi:10.1109/gcce46687.2019.9015542 · Cited by 9 · see citing works

Aligning Explanations for Recommendation with Rating and Feature via Maximizing Mutual Information

Zhao, Y., Sun, Y., Han, R., Jiang, F., Guan, L., Li, X., Lin, W., Ma, W., & Mao, J. (2024) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3627673.3679663 · Cited by 8 · see citing works

Aspect-Level Sentiment-Controllable Review Generation with Mutual Learning Framework

Chen, H., Lin, Y., Qi, F., Hu, J., Li, P., Zhou, J., & Sun, M. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i14.17497 · Cited by 8 · see citing works

Multimodal Review Generation with Privacy and Fairness Awareness

Vu, X.-S., Nguyen, T.-S., Le, D.-T., & Jiang, L. (2020) · International Conference on Computational Linguistics · doi:10.18653/v1/2020.coling-main.37 · Cited by 8 · see citing works

Personalized Transformer for Explainable RecommendationPreprint

Li, L., Zhang, Y., & Chen, L. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.11601 · Cited by 8 · see citing works

J-Recs: Principled and Scalable Recommendation Justification

Park, N., Kan, A., Faloutsos, C., & Xin, D. (2020) · Proceedings · doi:10.1109/icdm50108.2020.00151 · Cited by 7 · see citing works

Toward Explainable Recommendations: Generating Review Text from Multicriteria Evaluation Data

Suzuki, T. J., Oyama, S., & Kurihara, M. (2018) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2018.8622439 · Cited by 7 · see citing works

Domain-Assisted Product Aspect Hierarchy Generation: Towards Hierarchical Organization of Unstructured Consumer Reviews

Yu, J., Zha, Z.-J., Wang, M., Wang, K., & Chua, T. (2011) · National University of Singapore · Cited by 91 · see citing works

Retrieval-Augmented Controllable Review Generation

Kim, J., Choi, S. L., Amplayo, R. K., & Hwang, S.-W. (2020) · International Conference on Computational Linguistics · doi:10.18653/v1/2020.coling-main.207 · Cited by 21 · see citing works

Domain Independent Model for Product Attribute Extraction from User Reviews using Wikipedia

Kovelamudi, S., Ramalingam, S., Sood, A., & Varma, V. (2011) · Cited by 45 · see citing works

Unsupervised Extraction of Attributes and Their Values from Product Description

Shinzato, K., & Sekine, S. (2013) · International Joint Conference on Natural Language Processing · Cited by 28 · see citing works

MAPLE: Enhancing Review Generation with Multi-Aspect Prompt LEarning in Explainable Recommendation

Yang, C.-W., Feng, Z., Lin, Y.-J., Chen, C. W., Wu, K.-D., Xu, H., Jui-Feng, Y., & Kao, H.-Y. (2025) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2025.acl-long.1535 · Cited by 3 · see citing works