papers
Publications (2)
cs.AI2026
AgentX: Towards Agent-Driven Self-Iteration of Industrial Recommender Systems
Changxin Lao, Fei Pan, Guozhuang Ma +59
Recommendation algorithm iteration is moving from an artisanal, engineer-bound process toward an industrialized research loop, but this transition remains blocked by a structural e…
cs.IR2026
From Understanding to Action: Feedback-Grounded Policy Discovery for Generative Recommendation
Zhi Chen, Minmao Wang, Xingchen Liu +8
The paper introduces a feedback‑driven framework that first extracts user intent and then discovers recommendation policies using outcome‑derived feedback, distilling this knowledg…
#generative recommendation#large language models#feedback‑driven policy discovery#intent modeling