Enhancing LLMs for Sequential Recommendation With Reversed User History and User Embeddings
Inspired by the successful applications of Large Language Models (LLMs) in various fields, LLMs for sequential recommendation have also become an active research area. Recent studies have focused on leveraging the powerful capabilities of LLMs to enhance their alignment with sequential recommendatio...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11050368/ |
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