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Language-Based User Profiles for Recommendation
The encoder LLM generates a compact natural-language profile of the user's interests from the user's rating history.
Sample Efficient Reinforcement Learning from Human Feedback via Active Exploration
Preference-based feedback is important for many applications in reinforcement learning where direct evaluation of a reward function is not feasible.
Representation Learning in Low-rank Slate-based Recommender Systems
Reinforcement learning (RL) in recommendation systems offers the potential to optimize recommendations for long-term user engagement.
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