Agent4POI generates context-conditioned multimodal affordance representations via a four-phase LLM agent, achieving 23.2% relative gains over baselines on POI benchmarks with reduced degradation under context shifts.
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A policy-grounded retrieval-augmented framework with SLM scoring generates real-time personalized facet suggestions that boost engagement and job search outcomes.
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Agent4POI: Agentic Context-Conditioned Affordance Reasoning for Multimodal Point-of-Interest Recommendation
Agent4POI generates context-conditioned multimodal affordance representations via a four-phase LLM agent, achieving 23.2% relative gains over baselines on POI benchmarks with reduced degradation under context shifts.
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Policy-Grounded Dynamic Facet Suggestions for Job Search
A policy-grounded retrieval-augmented framework with SLM scoring generates real-time personalized facet suggestions that boost engagement and job search outcomes.