CS3 strengthens two-tower retrievers via cycle-adaptive feature denoising, cross-tower mutual awareness, and cascade knowledge reuse, delivering consistent gains on public datasets and up to 8.36% revenue lift in production advertising at millisecond latency.
arXiv preprint arXiv:2007.16122 (2020)
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
baseline 1
citation-polarity summary
fields
cs.IR 2verdicts
UNVERDICTED 2roles
baseline 1polarities
baseline 1representative 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
-
CS3: Efficient Online Capability Synergy for Two-Tower Recommendation
CS3 strengthens two-tower retrievers via cycle-adaptive feature denoising, cross-tower mutual awareness, and cascade knowledge reuse, delivering consistent gains on public datasets and up to 8.36% revenue lift in production advertising at millisecond latency.
-
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.