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Code-Based English Models Surprising Performance on Chinese QA Pair Extraction Task

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arxiv 2401.10286 v3 pith:CRR6CJIT submitted 2024-01-16 cs.CL cs.AI

classification cs.CLcs.AI
keywords modelschinesecode-basedenglishextractionpairperformancetask
verification ladder T0 review T1 audit T2 compute T3 formal
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In previous studies, code-based models have consistently outperformed text-based models in reasoning-intensive scenarios. When generating our knowledge base for Retrieval-Augmented Generation (RAG), we observed that code-based models also perform exceptionally well in Chinese QA Pair Extraction task. Further, our experiments and the metrics we designed discovered that code-based models containing a certain amount of Chinese data achieve even better performance. Additionally, the capabilities of code-based English models in specified Chinese tasks offer a distinct perspective for discussion on the philosophical "Chinese Room" thought experiment.

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