Empowering Multi-step Reasoning across Languages via Program-Aided Language Models (2024.emnlp-main)
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| Challenge: | In-context learning methods elicit Large Language Models to solve tasks using provided demonstrations without parameter updates. |
| Approach: | They propose a method for aligning reasoning programs across languages using a double-step cross-lingual prompting mechanism. |
| Outcome: | The proposed method outperforms existing prompting methods and reduces interaction time. |
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