Primacy Effect of ChatGPT
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arXiv
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| Format: | Preprint |
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2023
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| _version_ | 1866916244848902144 |
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| author | Wang, Yiwei Cai, Yujun Chen, Muhao Liang, Yuxuan Hooi, Bryan |
| author_facet | Wang, Yiwei Cai, Yujun Chen, Muhao Liang, Yuxuan Hooi, Bryan |
| contents | Instruction-tuned large language models (LLMs), such as ChatGPT, have led to promising zero-shot performance in discriminative natural language understanding (NLU) tasks. This involves querying the LLM using a prompt containing the question, and the candidate labels to choose from. The question-answering capabilities of ChatGPT arise from its pre-training on large amounts of human-written text, as well as its subsequent fine-tuning on human preferences, which motivates us to ask: Does ChatGPT also inherits humans' cognitive biases? In this paper, we study the primacy effect of ChatGPT: the tendency of selecting the labels at earlier positions as the answer. We have two main findings: i) ChatGPT's decision is sensitive to the order of labels in the prompt; ii) ChatGPT has a clearly higher chance to select the labels at earlier positions as the answer. We hope that our experiments and analyses provide additional insights into building more reliable ChatGPT-based solutions. We release the source code at https://github.com/wangywUST/PrimacyEffectGPT. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_13206 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Primacy Effect of ChatGPT Wang, Yiwei Cai, Yujun Chen, Muhao Liang, Yuxuan Hooi, Bryan Computation and Language Artificial Intelligence Instruction-tuned large language models (LLMs), such as ChatGPT, have led to promising zero-shot performance in discriminative natural language understanding (NLU) tasks. This involves querying the LLM using a prompt containing the question, and the candidate labels to choose from. The question-answering capabilities of ChatGPT arise from its pre-training on large amounts of human-written text, as well as its subsequent fine-tuning on human preferences, which motivates us to ask: Does ChatGPT also inherits humans' cognitive biases? In this paper, we study the primacy effect of ChatGPT: the tendency of selecting the labels at earlier positions as the answer. We have two main findings: i) ChatGPT's decision is sensitive to the order of labels in the prompt; ii) ChatGPT has a clearly higher chance to select the labels at earlier positions as the answer. We hope that our experiments and analyses provide additional insights into building more reliable ChatGPT-based solutions. We release the source code at https://github.com/wangywUST/PrimacyEffectGPT. |
| title | Primacy Effect of ChatGPT |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2310.13206 |