| Challenge: | elaborations are generated using language models that generate background knowledge that helps improve performance . human evaluations show that the quality of the generated ellaborations is high . |
| Approach: | They propose to finetune smaller language models to generate useful intermediate context . they compare a language model with an answer predictor and generate elaborations . human evaluations show that the quality of the generated ellaborations is high . |
| Outcome: | The proposed framework outperforms other models on commonsense questions on four commons sense benchmarks. |
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