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GLOBE: Evolving Structured Agentic Memory for E-commerce Product Optimization in Generative Search

Paper recorded by Signals 4 on 2026-10-16 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-16 on arXiv · recorded by Signals 4 on 2026-10-19

Category: cs.AI · 人工智能 · first seen 2026-10-19

Abstract

Optimizing product listings for generative search requires language agents not only to rewrite effectively but also to continually self-improve by retaining successful strategies across diverse categories. However, existing approaches often treat structured listings as free-form text, leaving effective strategies implicit in prompts, search trajectories, or rewritten outputs rather than accumulati

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#270 most recent of 960 cs.AI papers we have recorded · ↑ newer: Neural Expansion: A Unified Mechanism for How Deep Neural Networks Gen · ↓ older: On the possibilities and limitations of LLM-based multi-agent systems
Cite this page: GLOBE: Evolving Structured Agentic Memory for E-commerce Product Optimization in Generative Search: the #270 most recent of 960 cs.AI papers we have recorded (as of 2026-10-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/globe-evolving-structured-agentic-memory-for-e-commerce-product-optimization-in-.html
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