CoRCi: A New Framework for Cross-Domain Sequential Recommendation

A recent study presents CoRCi (Cross-Reconstruction for Coherent Interest), a dual-target model aimed at Cross-Domain Sequential Recommendation (CDSR). Accessible on arXiv (2608.09580v1), this research tackles the issue of data sparsity by facilitating the transfer of evolving user interests between related domains. Traditional approaches typically combine domain-specific sequences into a mixed-domain format, employing distinct encoders and separate loss aggregation per domain, which can exacerbate discrepancies and compromise the coherence of domain-invariant interests. CoRCi introduces a Cross-Reconstruction strategy to address these challenges, focusing on accurately capturing domain-invariant insights to enhance recommendation effectiveness. The framework is tailored for managing Seq2Seq query target pairs from different domains, a frequent source of errors in existing models. While the paper outlines the methodology, it does not detail experimental findings in the abstract. This work advances recommender systems, especially in cross-domain contexts, potentially influencing personalized content delivery across various applications.