Shortcut Learning in In-Context Learning: A Survey

• URL: http://arxiv.org/abs/2411.02018v1
• Date: Mon, 04 Nov 2024 12:13:04 GMT
• Title: Shortcut Learning in In-Context Learning: A Survey
• Authors: Rui Song, Yingji Li, Fausto Giunchiglia, Hao Xu,
• Abstract summary: Shortcut learning refers to the phenomenon where models employ simple, non-robust decision rules in practical tasks. This paper provides a novel perspective to review relevant research on shortcut learning in In-Context Learning (ICL)
• Score: 17.19214732926589
• License:
• Abstract: Shortcut learning refers to the phenomenon where models employ simple, non-robust decision rules in practical tasks, which hinders their generalization and robustness. With the rapid development of large language models (LLMs) in recent years, an increasing number of studies have shown the impact of shortcut learning on LLMs. This paper provides a novel perspective to review relevant research on shortcut learning in In-Context Learning (ICL). It conducts a detailed exploration of the types of shortcuts in ICL tasks, their causes, available benchmarks, and strategies for mitigating shortcuts. Based on corresponding observations, it summarizes the unresolved issues in existing research and attempts to outline the future research landscape of shortcut learning.

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