AgentRecommender: LLM Agents Enable Customizable Recommender Systems on the User Side
Recommender systems have traditionally been developed for platforms. However, this has given rise to many phenomena that may be advantageous for platform lock-in but are a nuisance to users, such as clickbait, filter bubbles, and the spread of fake news. Recently, user-side recommender systems have been proposed as a new paradigm for solving this problem. If users deploy their own recommender systems, they are no longer at the mercy of the platform's interests. However, building a user-side recommender system is not trivial; in particular, customizing one for oneself requires additional data. We propose AgentRecommender, a method that leverages the investigation capability and internal kn...
| Authors | Ryoma Sato |
|---|---|
| Primary category | cs.IR |
| Published | 25 September 2026 |
| Last updated at source | 25 September 2026 |
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