Knowledge is a Region in Weight Space for Fine-tuned Language Models (2023.findings-emnlp)
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| Challenge: | Specifically, language models that have been finetuned on the same dataset form a tight cluster in the weight space, while models finetuning on different datasets from the same underlying task form s looser clusters. |
| Approach: | They analyze the weight space and the underlying loss landscape of different models to determine how they are interconnected and how they perform. |
| Outcome: | The proposed method improves accuracy on 11 out of 12 datasets by starting from the center of the region, if not more, than using the pretrained model. |
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