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Generative chat models, such as ChatGPT and GPT-4, have revolutionizednatural language generation (NLG) by incorporating instructions and humanfeedback to achieve significant performance improvements. However, the lack ofstandardized evaluation benchmarks for chat models, particularly for Chineseand domain-specific models, hinders their assessment and progress. To addressthis gap, we introduce the Chinese Generative Chat Evaluation (CGCE) benchmark,focusing on general and financial domains. The CGCE benchmark encompassesdiverse tasks, including 200 questions in the general domain and 150 specificprofessional questions in the financial domain. Manual scoring evaluatesfactors such as accuracy, coherence, expression clarity, and completeness. TheCGCE benchmark provides researchers with a standardized framework to assess andcompare Chinese generative chat models, fostering advancements in NLG research.

CGCE: A Chinese Generative Chat Evaluation Benchmark for General and Financial Domains