R2MED is the first benchmark for reasoning-driven medical retrieval, where even top models reach only 41.4 nDCG@10 on queries requiring inference beyond lexical or semantic overlap.
InProceedings of the 17th ACM conference on Information and knowledge management, pages 143–152
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R2MED: A Benchmark for Reasoning-Driven Medical Retrieval
R2MED is the first benchmark for reasoning-driven medical retrieval, where even top models reach only 41.4 nDCG@10 on queries requiring inference beyond lexical or semantic overlap.
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A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions
The paper surveys hallucination in LLMs with an innovative taxonomy, factors, detection methods, benchmarks, mitigation strategies, and open research directions.