4 papers · 1 filter
RecEvolve: A Knowledge-Driven Autonomous Agent System for Recommender Systems
Weidi Pan, He Ma, Shuhao Ye +6
The rise of agentic AI has catalyzed a shift toward self-iterating systems, opening new frontiers for the autonomous optimization of production recommender models. This paper prese…
PLUM: Adapting Pre-trained Language Models for Industrial-scale Generative Recommendations
Ruining He, Lukasz Heldt, Lichan Hong +20
Large Language Models (LLMs) pose a new paradigm of modeling and computation for information tasks. Recommendation systems are a critical application domain poised to benefit signi…
User Feedback Alignment for LLM-powered Exploration in Large-scale Recommendation Systems
Jianling Wang, Yifan Liu, Yinghao Sun +11
Exploration, the act of broadening user experiences beyond their established preferences, is challenging in large-scale recommendation systems due to feedback loops and limited sig…
LLMs for User Interest Exploration in Large-scale Recommendation Systems
Jianling Wang, Haokai Lu, Yifan Liu +9
Traditional recommendation systems are subject to a strong feedback loop by learning from and reinforcing past user-item interactions, which in turn limits the discovery of novel u…