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Personal LLM agents can significantly improve recommendation quality by mediating platform rankings with cross-platform history, but naive mediation introduces substantial harmful overrides.
Dense scaling and test-time reasoning tokens are overkill for retrieval: scaling multimodal embeddings along the expert axis beats Think-Then-Embed baselines while cutting active parameter counts by over 4脳.
CORAL automates the continual optimization of recommender systems, achieving improved user engagement and reduced costs without human intervention.
