Ling Leng
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The paper introduces a novel paradigm where a fine-tuned LLM acts as an ancillary predictor to forecast likely advertisers, significantly improving ad recommendation systems by augmenting candidate generation and providing priors for downstream ranking.
The paper introduces SCALR, a novel framework that generates synthetic user-item interaction data from a source domain to augment a target recommendation domain, significantly improving system performance in A/B tests.
Papers
Synthetic Data from Cross-Domain Events for Large-Scale Recommendation Systems
Xiangyu Wang, Yawen He, Shivendra Pratap Singh, Han Huang +11 more
The paper introduces SCALR, a novel framework that generates synthetic user-item interaction data from a source domain to augment a target recommendation domain, significantly improving system perform…