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Retrieval, Scoring, and Decoding Shape Performance and Stability in LLM-based Conversational Recommendation
Large language models (LLMs) are increasingly used as rerankers in conversational recommender systems, yet measured gains depend strongly on the retrieval and inference protocol. On the ReDial conversational movie recommendation benchmark, we compare proprietary, open-weight, and fine-tuned LLM rera
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