Embedding Domain Knowledge for Large Language Models via Reinforcement Learning from Augmented Generation (2025.emnlp-main)
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| Challenge: | Existing approaches to embed knowledge into large language models have some limitations . static nature of training data and lack of knowledge in domains create knowledge gaps . |
| Approach: | They propose a method that iteratively cycles between sampling generations and optimizing the model through calculated rewards. |
| Outcome: | The proposed method outperforms baseline approaches on medical, legal, astronomy, and current events datasets. |
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