SyncAI.news, a Varaisys broadcasting
RecGroupMemory: Feedback-Aware Cohort Memory for E-Commerce Recommendation
WZ

Wendong Zhang, Weipeng Huang, Zhixin Ma, Bin Zhang, Dimin Wang

· 1 min read

ResearcharXiv cs.AI

RecGroupMemory: Feedback-Aware Cohort Memory for E-Commerce Recommendation

arXiv:2611.02453v1 Announce Type: new Abstract: Cohort memory can support LLM-based recommendation planning through group-level user profiles and advice. As outcome feedback becomes available, this guidance may need to be updated while preserving the underlying observations. We present RecGroupMemory, a workflow that provides this memory to an orchestration LLM and separates memory construction from feedback-based revision. It uses feedback from the previous day to revise decision guidance, while validation checks keep selected source values unchanged. Online comparisons were conducted among Taobao users with low purchasing power selected by the business team. Relative to a no-memory baseline, memory without feedback and memory with feedback showed increases of 1.58% and 1.78%, respectively, in the number of guided transaction users.

Original source

This story was published by arXiv cs.AI and written by Wendong Zhang, Weipeng Huang, Zhixin Ma, Bin Zhang, Dimin Wang. SyncAI.news shows a preview; the complete article is on the publisher's site.

Read the full story on arxiv.org

Similar News