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Instantaneously adapt recommendation models to user requests without retraining, achieving superior performance with minimal overhead.
High sample efficiency in learning-to-rank can be achieved without the headaches of custom gradients, making RL more accessible for practitioners.
LLMs can now generate more relevant and factual movie recommendations by dynamically bridging retrieval and generation with a novel reinforcement learning approach.
