Generating and comparing label-by-label explanations in the prompt improves out-of-distribution accuracy of in-context learning on most tested NLU benchmarks, at the cost of in-distribution performance and higher inference cost.
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Exploring Explanations Improves the Robustness of In-Context Learning
Generating and comparing label-by-label explanations in the prompt improves out-of-distribution accuracy of in-context learning on most tested NLU benchmarks, at the cost of in-distribution performance and higher inference cost.