Effectiveness of Zero-shot-CoT in Japanese Prompts
원문 초록
We compare the effectiveness of zero-shot Chain-of-Thought (CoT) prompting in Japanese and English using ChatGPT-3.5 and 4o-mini. The technique of zero-shot CoT, which involves appending a phrase such as "Let's think step by step" to a prompt to encourage reasoning before answering, has been shown to offer LLM performance improvements in mathematical and reasoning tasks, particularly in English. We investigate how these effects transfer to Japanese using the Japanese Multi-task Language Understanding Benchmark (JMMLU) and the Multi-task Language Understanding Benchmark (MMLU). Our results show that while zero-shot CoT prompting can lead to notable performance gains for some prompt categories in GPT-3.5, its impact in GPT-4o-mini is associated with significant performance declines. However, for Japanese prompts there remain certain categories, such as college mathematics and abstract algebra, that still exhibit improvements, despite the broader trend of diminishing effectiveness in more advanced models.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
TUMLU: A Unified and Native Language Understanding Benchmark for Turkic Languages
MMLU-CF: A Contamination-free Multi-task Language Understanding Benchmark
Llama 3 Meets MoE: Efficient Upcycling
Measuring Hong Kong Massive Multi-Task Language Understanding
IndicMMLU-Pro: Benchmarking Indic Large Language Models on Multi-Task Language Understanding
Reasoning Beyond Bias: A Study on Counterfactual Prompting and Chain of Thought Reasoning
토론
이 논문과 연결된 포럼 글이 아직 없습니다.