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Figure 29: Edit distance (ED) for instruction-tuned (IT) and non-instruction-tuned (Non-IT) Falcon models using
the open prompt in the settings of zero-shot (ZS) and few-shot (FS).

Figure 30: Exact match accuracy (EMA) for instruction-tuned (IT) and non-instruction-tuned (Non-IT) LLaMA
models using the closed prompt in the settings of zero-shot (ZS) and few-shot (FS).

Figure 31: Exact match accuracy (EMA) for instruction-tuned (IT) and non-instruction-tuned (Non-IT) LLaMA
models using the closed adversarial prompt in the settings of zero-shot (ZS) and few-shot (FS).

Figure 32: Exact match accuracy (EMA) for instruction-tuned (IT) and non-instruction-tuned (Non-IT) LLaMA
models using the open prompt in the settings of zero-shot (ZS) and few-shot (FS).

Figure 33: BERTScore accuracy (BSA) for instruction-tuned (IT) and non-instruction-tuned (Non-IT) LLaMA
models using the closed prompt in the settings of zero-shot (ZS) and few-shot (FS).

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AreEmergentAbilitiesinLarge Language Models just In-Context