# A Universal Framework for Offline Serendipity Evaluation in Recommender Systems via Large Language Models

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-universal-framework-for-offline-serendipity-evaluation-in-recommender-systems/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yu Tokutake,Kazushi Okamoto,Koichi Harada,Atsushi Shibata,Koki Karube |
| Citations | 0 |
| DOI | 10.1145/3746252.3760911 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | gold |
| OA URL | https://doi.org/10.1145/3746252.3760911 |
| OpenAlex ID | https://openalex.org/W4416017325 |
| Type | conference-paper |
| Year | 2025 |

## Paper authors

- [Koki Karube](https://scholariq.org/researchers/koki-karube/)

## Paper primary topic

- [Recommender Systems and Techniques](https://scholariq.org/topics/recommender-systems-and-techniques/)

## Paper topics

- [Recommender Systems and Techniques](https://scholariq.org/topics/recommender-systems-and-techniques/)
- [Explainable Artificial Intelligence (XAI)](https://scholariq.org/topics/explainable-artificial-intelligence-xai/)
- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.