COPE: Continual Personalization of LLMs under Sparse User Feedback via User Embeddings and Self-Evaluation
arXiv 2609.26853v1•9d1a46b7282bb660dcb745a64a905c86a790b6ab6797c35021df89700dc6f59d
Paper metadata
- arXiv ID
- 2609.26853
- Version
- v1
- Category
- cs.AI, cs.LG
- Authors
- Ruike Cao, Fugen Yao, Liang Dong, Jian Xu, Guanjun Jiang, Li Xiao
- Publication date
- 2026-09-24T04:00:00Z
- Source identifier
- 2609.26853v1
- Public record ID
- record:sha256:9d1a46b7282bb660dcb745a64a905c86a790b6ab6797c35021df89700dc6f59d
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Evidence and limitations
- Source ID
- arxiv_research
- Record identifier
- 9d1a46b7282bb660dcb745a64a905c86a790b6ab6797c35021df89700dc6f59d
- Record type
- Source metadata
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