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cs.IR2026
From Valid to Useful: Post-Verification Acquisition for Recursive Self-Improving Recommendation
Tonmoy Hasan, Taylor Foust, Shao Tang +6
Sequential recommenders can generate synthetic interaction sequences and retrain on the augmented corpus in a recursive self-improvement loop. To limit error accumulation, current…
cs.IR2026
Semantic IDs for Recommender Systems at Snapchat: Use Cases, Technical Challenges, and Design Choices
Clark Mingxuan Ju, Tong Zhao, Leonardo Neves +15
Effective item identifiers (IDs) are an important component for recommender systems (RecSys) in practice, and are commonly adopted in many use cases such as retrieval and ranking.…
cs.LG2026
Exploiting ID-Text Complementarity via Ensembling for Sequential Recommendation
Liam Collins, Bhuvesh Kumar, Clark Mingxuan Ju +4
Modern Sequential Recommendation (SR) models commonly utilize modality features to represent items, motivated in large part by recent advancements in language and vision modeling.…