PersonaRAG: Enhancing Retrieval-Augmented Generation Systems with User-Centric Agents
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866917204268679168 |
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| author | Zerhoudi, Saber Granitzer, Michael |
| author_facet | Zerhoudi, Saber Granitzer, Michael |
| contents | Large Language Models (LLMs) struggle with generating reliable outputs due to outdated knowledge and hallucinations. Retrieval-Augmented Generation (RAG) models address this by enhancing LLMs with external knowledge, but often fail to personalize the retrieval process. This paper introduces PersonaRAG, a novel framework incorporating user-centric agents to adapt retrieval and generation based on real-time user data and interactions. Evaluated across various question answering datasets, PersonaRAG demonstrates superiority over baseline models, providing tailored answers to user needs. The results suggest promising directions for user-adapted information retrieval systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_09394 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | PersonaRAG: Enhancing Retrieval-Augmented Generation Systems with User-Centric Agents Zerhoudi, Saber Granitzer, Michael Information Retrieval Large Language Models (LLMs) struggle with generating reliable outputs due to outdated knowledge and hallucinations. Retrieval-Augmented Generation (RAG) models address this by enhancing LLMs with external knowledge, but often fail to personalize the retrieval process. This paper introduces PersonaRAG, a novel framework incorporating user-centric agents to adapt retrieval and generation based on real-time user data and interactions. Evaluated across various question answering datasets, PersonaRAG demonstrates superiority over baseline models, providing tailored answers to user needs. The results suggest promising directions for user-adapted information retrieval systems. |
| title | PersonaRAG: Enhancing Retrieval-Augmented Generation Systems with User-Centric Agents |
| topic | Information Retrieval |
| url | https://arxiv.org/abs/2407.09394 |