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When LLM-Inferred User Context Adds Value in Production Streaming Recommendation
Contextual information in recommender systems is shifting from static, predefined variables toward latent representations inferred from behavior. Large language models support this shift by rendering an unstructured interaction history as a natural-language summary, which yields a thematic user cont
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