Author

Shaghayegh Agah

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Preprint Sep 2026

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 context that can be enco...

M. Sabouri, Neeraj Sharma, Sardar Hamidian et al. · 0 citations

Preprint Sep 2026

Routing Between Generative and Collaborative User Profiles: A Serving-Time Gate for Controllable Novelty

Large language models (LLMs) enable rich semantic user profiles for recommendation, but such profiles are more expensive to generate and are not necessarily desirable to deploy uniformly. We study whether LLM-generated profiles can instead be invoked selectively within a production recommendation pipeline. Using a real...

M. Sabouri, Neeraj Sharma, Sardar Hamidian et al. · 0 citations

Preprint Sep 2026

When LLM-Based User Profiling Adds Value in Production Streaming Recommendation

A systematic comparison of four semantic user-profiling strategies, factorially crossed across representation type and temporal handling, evaluated on a real-world production dataset reveals how these strategies differ across user behavior types, across both accuracy and beyond-accuracy dimensions of recommendation qua...

M. Sabouri, Neeraj Sharma, Sardar Hamidian et al. · 2 citations