A User-Centric Benchmark for Evaluating Large Language Models

arXiv:2404.13940v1 Announce Type: new
Abstract: Large Language Models (LLMs) are essential tools to collaborate with users on different tasks. Evaluating their performance to serve users' needs in real-world scenarios is important. While many benchmarks have been created, they mainly focus on specific predefined model abilities. Few have covered the intended utilization of LLMs by real users. To address this oversight, we propose benchmarking LLMs from a user perspective in both dataset construction and evaluation designs. We first collect 1863 real-world …

arxiv benchmark cs.cl language language models large language large language models type