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cs.CL2026
Toward Robust In-Context Learning: Leveraging Out-of-distribution Proxies for Target Inaccessible Demonstration Retrieval
Hao Xu, Rite Bo, Fausto Giunchiglia +2
Although studies have demonstrated that Large Language Models (LLMs) can perform well on Out-of-Distribution (OOD) tasks, their advantage tends to diminish as the distribution shif…
cs.CL2024
Shortcut Learning in In-Context Learning: A Survey
Rui Song, Yingji Li, Lida Shi +2
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 rap…