Hugging Face Trending Papers
IntentGEO: Intent-aware Generative Engine Optimization for Recommendation
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arXiv AI
Oct 28
Role-Augmented Intent-Driven Generative Search Engine Optimization
The paper introduces RAID, a Role-Augmented Intent-Driven Generative Search Engine Optimization method that improves web content visibility without needing target queries or GSE feedback. RAID infers a primary retrieval intent from source content, refines it through a 4W multi-role deep reflection on prospective searchers’ information needs, and jointly plans and rewrites the content. Evaluated on 100 samples and 500 queries, RAID outperforms nine GEO rewriting strategies, achieving higher relative improvement scores and effective optimization rates.
arXiv AI
Sep 24
Query Implied Generative Engine Optimization
The paper "Query Implied Generative Engine Optimization" introduces QI‑GEO, a method that infers user intent directly from documents to enhance visibility in Generative Search Engines. By approximating a document’s intent space, QI‑GEO identifies missing yet relevant content, improving objective scores by up to 15.9% and subjective scores by up to 17.6% on GEO‑Bench datasets. The approach yields nearly twice as many citation gains as losses, demonstrating that document‑derived intent approximations can boost content visibility without explicit query inputs.
arXiv AI
Sep 1
Agent2UCB: Agentic System for Generative Engine Optimization
Agent2UCB is a new agentic system designed for Generative Engine Optimization (GEO), which refines content to boost its likelihood of being cited or summarized by generative AI search engines. The system autonomously evaluates nine GEO strategies for each content item, selects the most effective one, and speeds up this selection using a bandit-based Agent2UCB policy that blends large language model priors with real-time reward signals. Additionally, it offers a lightweight, text-only SEO readiness check that assesses readability, topical coverage, and EEAT-style credibility, and experiments on GEO-Bench demonstrate consistent visibility gains while maintaining SEO quality.
arXiv AI
Jul 2
EcoGEO: Trajectory-Aware Evidence Ecosystems for Web-Enabled LLM Search Agents
arXiv:2605. 12887v2 Announce Type: replace-cross Abstract: Web-enabled LLM agents are changing how online information influences search outcomes.
arXiv AI
Sep 15
Generate to Explore, Select to Exploit: Aligning LLM-based Headline Generation with Personalized Recommendation
arXiv:2609.15094v1 Announce Type: cross Abstract: In industrial recommendation feeds, presenting a static headline for an item often fails to satisfy the diverse, multimodal interests of the user pop...
arXiv AI
Aug 18
Dear Algo: A Precision-First Agentic Intent Layer for Unified Search and Recommendation
arXiv:2608. 15877v1 Announce Type: new Abstract: Search and recommendation serve a shared discovery objective but encode intent differently.