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Few-Shot Example Selection Metrics Design
Pretrained language models benefit from complexity-based prompt selection for improved few-shot learning performance.
Few-Shot Example Selection Metrics Design
Pretrained language models benefit from complexity-based prompt selection for improved few-shot performance.
Enhancing Few-Shot Example Selection with Complexity-Based Metrics
The author proposes a complexity-based prompt selection approach for sequence tagging tasks to improve few-shot learning capabilities of pretrained language models. By aligning the syntactico-semantic complexity of examples with test sentences, significant performance gains are achieved.
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