Primacy Effect of ChatGPT

• URL: http://arxiv.org/abs/2310.13206v2
• Date: Tue, 14 May 2024 17:17:17 GMT
• Title: Primacy Effect of ChatGPT
• Authors: Yiwei Wang, Yujun Cai, Muhao Chen, Yuxuan Liang, Bryan Hooi,
• Abstract summary: We study the primacy effect of ChatGPT: the tendency of selecting 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.
• Score: 69.49920102917598
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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