13 citations · 21 across the 6 of their papers we have counts for
5 papers · 1 filter
NOVA: A Verification-Aware Agent Harness for Architecture Evolution in Industrial Recommender Systems
Shaohua Liu, Liang Fang, Yilong Sun +16
Industrial advertising recommender systems are continually improved through architecture modifications, yet production iteration remains expert-intensive because coordinated change…
Unified Representation Learning for Multi-Intent Diversity and Behavioral Uncertainty in Recommender Systems
Wei Xu, Jiasen Zheng, Junjiang Lin +2
This paper addresses the challenge of jointly modeling user intent diversity and behavioral uncertainty in recommender systems. A unified representation learning framework is propo…
ADSNet: Cross-Domain LTV Prediction with an Adaptive Siamese Network in Advertising
Ruize Wang, Hui Xu, Ying Cheng +6
Advertising platforms have evolved in estimating Lifetime Value (LTV) to better align with advertisers' true performance metric. However, the sparsity of real-world LTV data presen…
RecAI: Leveraging Large Language Models for Next-Generation Recommender Systems
Jianxun Lian, Yuxuan Lei, Xu Huang +3
This paper introduces RecAI, a practical toolkit designed to augment or even revolutionize recommender systems with the advanced capabilities of Large Language Models (LLMs). RecAI…
Knowledge Plugins: Enhancing Large Language Models for Domain-Specific Recommendations
Jing Yao, Wei Xu, Jianxun Lian +3
The significant progress of large language models (LLMs) provides a promising opportunity to build human-like systems for various practical applications. However, when applied to s…