Automating Personalization: Prompt Optimization for Recommendation Reranking
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916675146743808 |
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| author | Wang, Chen Yang, Mingdai Liu, Zhiwei Li, Pan Pang, Linsey Wen, Qingsong Yu, Philip |
| author_facet | Wang, Chen Yang, Mingdai Liu, Zhiwei Li, Pan Pang, Linsey Wen, Qingsong Yu, Philip |
| contents | Modern recommender systems increasingly leverage large language models (LLMs) for reranking to improve personalization. However, existing approaches face two key limitations: (1) heavy reliance on manually crafted prompts that are difficult to scale, and (2) inadequate handling of unstructured item metadata that complicates preference inference. We present AGP (Auto-Guided Prompt Refinement), a novel framework that automatically optimizes user profile generation prompts for personalized reranking. AGP introduces two key innovations: (1) position-aware feedback mechanisms for precise ranking correction, and (2) batched training with aggregated feedback to enhance generalization. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_03965 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Automating Personalization: Prompt Optimization for Recommendation Reranking Wang, Chen Yang, Mingdai Liu, Zhiwei Li, Pan Pang, Linsey Wen, Qingsong Yu, Philip Information Retrieval Modern recommender systems increasingly leverage large language models (LLMs) for reranking to improve personalization. However, existing approaches face two key limitations: (1) heavy reliance on manually crafted prompts that are difficult to scale, and (2) inadequate handling of unstructured item metadata that complicates preference inference. We present AGP (Auto-Guided Prompt Refinement), a novel framework that automatically optimizes user profile generation prompts for personalized reranking. AGP introduces two key innovations: (1) position-aware feedback mechanisms for precise ranking correction, and (2) batched training with aggregated feedback to enhance generalization. |
| title | Automating Personalization: Prompt Optimization for Recommendation Reranking |
| topic | Information Retrieval |
| url | https://arxiv.org/abs/2504.03965 |