Poison-RAG: Adversarial Data Poisoning Attacks on Retrieval-Augmented Generation in Recommender Systems

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Deldjoo, Y., Di Noia, T., Merra, F.A.: A survey on Adversarial Recommender Systems: from attack/defense Strategies to Generative Adversarial Networks. ACM Computing Surveys (CSUR) (2), 1–38 (2022)

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Di Palma, D.: Retrieval-augmented recommender system: Enhancing recommender systems with large language models. In: Proceedings of the 17th ACM Conference on Recommender Systems. pp. 1369–1373 (2023)

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Lin, J., Dai, X., Xi, Y., Liu, W., Chen, B., Zhang, H., Liu, Y., Wu, C., Li, X., Zhu, C., et al.: How can recommender systems benefit from large language models: A survey. arXiv preprint arXiv:2306.05817 (2023)

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AI, T.: A taxonomy of retrieval-augmented generation. Towards AI (2024), https://pub.towardsai.net/a-taxonomy-of-retrieval-augmented-generation-a39eb2c4e2ab , accessed: 2024-11-08

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Anderson, M., Amit, G., Goldsteen, A.: Is My Data in Your Retrieval Database? Membership Inference Attacks Against Retrieval Augmented Generation. arXiv preprint arXiv:2405.20446 (2024)

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Chaudhari, H., Severi, G., Abascal, J., Jagielski, M., Choquette-Choo, C.A., Nasr, M., Nita-Rotaru, C., Oprea, A.: Phantom: General Trigger Attacks on Retrieval Augmented Language Generation. arXiv preprint arXiv:2405.20485 (2024)

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Chen, Z., Liu, J., Liu, H., Cheng, Q., Zhang, F., Lu, W., Liu, X.: Black-Box Opinion Manipulation Attacks to Retrieval-Augmented Generation of Large Language Models. arXiv preprint arXiv:2407.13757 (2024)

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Deldjoo, Y.: Understanding Biases in ChatGPT-based Recommender Systems: Provider Fairness, Temporal stability, and Recency. ACM Transactions on Recommender Systems (2024). https://doi.org/10.1145/3690655

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Deldjoo, Y., He, Z., McAuley, J., Korikov, A., Sanner, S., Ramisa, A., Vidal, R., Sathiamoorthy, M., Kasirzadeh, A., Milano, S.: A Review of Modern Recommender Systems using Generative Models (Gen-RecSys). In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. pp. 6448–6458 (2024)

Fan, W., Ding, Y., Ning, L., Wang, S., Li, H., Yin, D., Chua, T.S., Li, Q.: A survey on rag meeting llms: Towards retrieval-augmented large language models. In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. pp. 6491–6501 (2024)

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Li, Y., Liu, G., Wang, C., Yang, Y.: Generating Is Believing: Membership Inference Attacks against Retrieval-Augmented Generation. arXiv preprint arXiv:2406.19234 (2024)

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2024

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Xue, J., Zheng, M., Hu, Y., Liu, F., Chen, X., Lou, Q.: BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models. arXiv preprint arXiv:2406.00083 (2024)

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Zou, W., Geng, R., Wang, B., Jia, J.: Poisonedrag: Knowledge corruption attacks to retrieval-augmented generation of large language models. arXiv preprint arXiv:2402.07867 (2024)

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2024

Later among the works it cites.