#recommendation systems

'Real-world case studies show context engineering driving error reduction, productivity gains, cost savings, and better user experiences by grounding LLMs with dynamic, multi-source data.'

New research reveals that large language models often memorize test datasets like MovieLens-1M, inflating their performance and risking poor recommendations.