SRBench is a multi-dimensional benchmark for sequential recommendation that uses prompt engineering and a coupled extraction mechanism to support fair evaluation of both neural-network and LLM-based models across accuracy, fairness, stability, and efficiency.
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SRBench: A Comprehensive Benchmark for Sequential Recommendation with Large Language Models
SRBench is a multi-dimensional benchmark for sequential recommendation that uses prompt engineering and a coupled extraction mechanism to support fair evaluation of both neural-network and LLM-based models across accuracy, fairness, stability, and efficiency.