LLM rerankers in cold-start recsys show recall@200 of 0.109, concentrate on only 3 items, and are beaten by popularity baselines (HR@10 0.268 vs 0.008).
MS MARCO: A Human Generated Machine Reading Comprehension Dataset,
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Diagnosing LLM-based Rerankers in Cold-Start Recommender Systems: Coverage, Exposure and Practical Mitigations
LLM rerankers in cold-start recsys show recall@200 of 0.109, concentrate on only 3 items, and are beaten by popularity baselines (HR@10 0.268 vs 0.008).