对比SASRec与BSARec，发现频率增强项提升推荐效果但增幅有限。
A Systematic Replicability and Comparative Study of BSARec and SASRec for Sequential Recommendation
- 统一基于EasyRec重实现模型，确保公平对比
- BSARec因引入频率偏置项，性能优于SASRec
- 强调实现细节对结果可复现性的重要性
本研究旨在对比两种序列推荐模型：基于自注意力的SASRec与超越自注意力的BSARec，以检验后者中引入的频率增强机制是否带来实际性能提升。所有模型均基于EasyRec框架重新实现，确保比较的公平性与可复现性。实验结果表明，尽管引入频率偏置项后BSARec性能优于SASRec，但其提升幅度低于原作者报告的水平。该工作不仅梳理了现有方法，更凸显了实现细节在性能评估中的关键作用。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。