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title: "LACRM: LLM-Guided Mining of Directed Advertiser Competition Relationships in E-Commerce Advertising"
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published_at: "2026-10-14T04:00:00.000Z"
category: "Research"
topics: ["llm"]
source_urls: ["https://arxiv.org/abs/2610.13959"]
summary: "Researchers propose LACRM, a framework that uses large language models to build directed competition graphs with continuous edge intensities for e-commerce advertising. The three-stage pipeline employs LLM-driven role-separated profiling to enable asymmetric multi-route retrieval of both realized and latent rivals, and incorporates listwise learning-to-rank aligned with temporal auction behavior to model directed competition intensity."
---

# LACRM: LLM\-Guided Mining of Directed Advertiser Competition Relationships in E\-Commerce Advertising

> [Open the canonical story](<https://aidr.today/0ff24cbd?lang=en>)

**Published:** 2026-10-14T04:00:00.000Z
**Category:** Research
**Topics:** llm

## Summary

Researchers propose LACRM, a framework that uses large language models to build directed competition graphs with continuous edge intensities for e\-commerce advertising\. The three\-stage pipeline employs LLM\-driven role\-separated profiling to enable asymmetric multi\-route retrieval of both realized and latent rivals, and incorporates listwise learning\-to\-rank aligned with temporal auction behavior to model directed competition intensity\.

## Sources

- [Story source](<https://arxiv.org/abs/2610.13959>)