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New ANGLE framework enhances real-time ad retrieval with LLM-driven hierarchy

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new framework called ANGLE (A uNified Generation-discriminative-ranking reaL-time rEtrieval) to improve real-time sponsored search ad retrieval. This framework addresses limitations in traditional multi-stage systems and existing LLM-based methods by using hierarchical text representations that capture both commercial intent and fine-grained ad details. ANGLE integrates retrieval, relevance, and ranking within a single LLM, leading to more precise ad ranking and improved performance in real-world scenarios, including a 1.81% increase in consumption and a 2.16% increase in GMV. AI

IMPACT This framework could lead to more efficient and effective ad targeting in real-time search environments.

RANK_REASON The cluster contains a research paper detailing a new framework for information retrieval. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New ANGLE framework enhances real-time ad retrieval with LLM-driven hierarchy

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The cluster contains a research paper detailing a new framework for information retrieval. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Haiyang Wu ·

    One-Step Retrieval Framework for Real-Time Sponsored Search Ads Using Hierarchical Text Representations

    Traditional retrieval systems typically use multi-stage cascading architectures (MCA), where each module is optimized independently, leading to inconsistent objectives and the premature elimination of high-potential candidates. Recent LLM-based generation methods offer end-to-end…

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