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cs.IR2024★ 5 cited
Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policies
Chih-Wei Hsu, Martin Mladenov, Ofer Meshi +8
Evaluation of policies in recommender systems typically involves A/B testing using live experiments on real users to assess a new policy's impact on relevant metrics. This ``gold s…
cs.IR2024
Item-Language Model for Conversational Recommendation
Li Yang, Anushya Subbiah, Hardik Patel +5
Large-language Models (LLMs) have been extremely successful at tasks like complex dialogue understanding, reasoning and coding due to their emergent abilities. These emergent abili…