Over-Reasoning and Redundant Calculation of Large Language Models (2024.eacl-short)
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| Challenge: | Large language models (LLMs) can solve problems step-by-step, but it is unclear whether they know when to use CoT and whether they are always necessary. |
| Approach: | They propose to use LLMs to generate redundant calculations and reasoning on a manually constructed math QA dataset, GSM8K-Zero. |
| Outcome: | The proposed model generates redundant calculations and reasoning on a manually constructed math QA dataset, but it is unclear whether it is necessary to use CoT reasoning. |
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