[WSDM 2024 Oral] This is our Pytorch implementation for the paper: "Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation".
Home Page: https://arxiv.org/pdf/2310.14318.pdf
License: MIT License
From the performance comparison (Table 2 in the paper), it is obvious that only DuoRec and ICSRec use CE loss, while other baseline models employ BCE loss. However, models equipped with BCE loss inherently exhibit inferior performance than ones with CE loss. As a result, this unfair comparison may lead to unreliable experimental results.
你好，这篇工作github上面的训练超参数只有Beauty数据集的，能提供其他数据集的训练超参数吗？非常感谢！还是说每个数据集的训练超参数都一样呢。
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