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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.13665 |
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| _version_ | 1866908966004457472 |
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| author | Ng, Tze-Kean Khoo, Joshua Teng-Khing Sun, Aixin |
| author_facet | Ng, Tze-Kean Khoo, Joshua Teng-Khing Sun, Aixin |
| contents | A good number of toolkits have been developed in Recommender Systems (RecSys) research to promote fair evaluation and reproducibility. However, recent critical examinations of RecSys evaluation protocols have raised concerns regarding the validity of existing evaluation pipelines. In this demonstration, we present RecNextEval, a reference implementation of an evaluation framework specifically designed for next-batch recommendation. RecNextEval utilizes a time-window data split to ensure models are evaluated along a global timeline, effectively minimizing data leakage. Our implementation highlights the inherent complexities of RecSys evaluation and encourages a shift toward model development that more accurately simulates production environments. The RecNextEval library and its accompanying GUI interface are open-source and publicly accessible. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_13665 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | RecNextEval: A Reference Implementation for Temporal Next-Batch Recommendation Evaluation Ng, Tze-Kean Khoo, Joshua Teng-Khing Sun, Aixin Information Retrieval A good number of toolkits have been developed in Recommender Systems (RecSys) research to promote fair evaluation and reproducibility. However, recent critical examinations of RecSys evaluation protocols have raised concerns regarding the validity of existing evaluation pipelines. In this demonstration, we present RecNextEval, a reference implementation of an evaluation framework specifically designed for next-batch recommendation. RecNextEval utilizes a time-window data split to ensure models are evaluated along a global timeline, effectively minimizing data leakage. Our implementation highlights the inherent complexities of RecSys evaluation and encourages a shift toward model development that more accurately simulates production environments. The RecNextEval library and its accompanying GUI interface are open-source and publicly accessible. |
| title | RecNextEval: A Reference Implementation for Temporal Next-Batch Recommendation Evaluation |
| topic | Information Retrieval |
| url | https://arxiv.org/abs/2604.13665 |