APG4RecSim automatically generates realistic user profiles for LLM-based recommendation simulations, outperforming manual baselines by up to 7% in nDCG@10 and 8% in JSD on three benchmark datasets.
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An LLM framework with RAG predicts query-specific validity horizons for web content expiration and shows gains in production A/B tests.
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Task-Aware Automated User Profile Generation for Recommendation Simulation Using Large Language Models
APG4RecSim automatically generates realistic user profiles for LLM-based recommendation simulations, outperforming manual baselines by up to 7% in nDCG@10 and 8% in JSD on three benchmark datasets.
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RAG-Enhanced Large Language Models for Dynamic Content Expiration Prediction in Web Search
An LLM framework with RAG predicts query-specific validity horizons for web content expiration and shows gains in production A/B tests.