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cs.IR2025
Counterfactual Reciprocal Recommender Systems for User-to-User Matching
Kazuki Kawamura, Takuma Udagawa, Kei Tateno
Reciprocal recommender systems (RRS) in dating, gaming, and talent platforms require mutual acceptance for a match. Logged data, however, over-represents popular profiles due to pa…
cs.IR2025
Not Just What, But When: Integrating Irregular Intervals to LLM for Sequential Recommendation
Wei-Wei Du, Takuma Udagawa, Kei Tateno
Time intervals between purchasing items are a crucial factor in sequential recommendation tasks, whereas existing approaches focus on item sequences and often overlook by assuming…