A Systematic Replicability and Comparative Study of BSARec and SASRec for Sequential Recommendation
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866916796993372160 |
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| author | D'Ercoli, Chiara Di Teodoro, Giulia Siciliano, Federico |
| author_facet | D'Ercoli, Chiara Di Teodoro, Giulia Siciliano, Federico |
| contents | This study aims at comparing two sequential recommender systems: Self-Attention based Sequential Recommendation (SASRec), and Beyond Self-Attention based Sequential Recommendation (BSARec) in order to check the improvement frequency enhancement - the added element in BSARec - has on recommendations. The models in the study, have been re-implemented with a common base-structure from EasyRec, with the aim of obtaining a fair and reproducible comparison. The results obtained displayed how BSARec, by including bias terms for frequency enhancement, does indeed outperform SASRec, although the increases in performance obtained, are not as high as those presented by the authors. This work aims at offering an overview on existing methods, and most importantly at underlying the importance of implementation details for performance comparison. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_14692 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Systematic Replicability and Comparative Study of BSARec and SASRec for Sequential Recommendation D'Ercoli, Chiara Di Teodoro, Giulia Siciliano, Federico Information Retrieval This study aims at comparing two sequential recommender systems: Self-Attention based Sequential Recommendation (SASRec), and Beyond Self-Attention based Sequential Recommendation (BSARec) in order to check the improvement frequency enhancement - the added element in BSARec - has on recommendations. The models in the study, have been re-implemented with a common base-structure from EasyRec, with the aim of obtaining a fair and reproducible comparison. The results obtained displayed how BSARec, by including bias terms for frequency enhancement, does indeed outperform SASRec, although the increases in performance obtained, are not as high as those presented by the authors. This work aims at offering an overview on existing methods, and most importantly at underlying the importance of implementation details for performance comparison. |
| title | A Systematic Replicability and Comparative Study of BSARec and SASRec for Sequential Recommendation |
| topic | Information Retrieval |
| url | https://arxiv.org/abs/2506.14692 |