GenLI generates diverse target-independent interest distributions via an IGM, retrieves behaviors with O(1) lookup in BRM, and fuses via IFM gating to balance accuracy and efficiency in CTR prediction.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.IR 2verdicts
UNVERDICTED 2representative citing papers
OneRec unifies retrieval and ranking in a generative recommender using session-wise decoding and iterative DPO-based preference alignment, achieving real-world gains on Kuaishou.
citing papers explorer
-
Generative Long-term User Interest Modeling for Click-Through Rate Prediction
GenLI generates diverse target-independent interest distributions via an IGM, retrieves behaviors with O(1) lookup in BRM, and fuses via IFM gating to balance accuracy and efficiency in CTR prediction.
-
OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment
OneRec unifies retrieval and ranking in a generative recommender using session-wise decoding and iterative DPO-based preference alignment, achieving real-world gains on Kuaishou.