Papers with ColD Fusion
ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning (2023.acl-long)
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| Challenge: | Pretraining has been shown to scale well with compute, data size and data diversity. |
| Approach: | They propose a method that provides benefits of multitask learning but leverages distributed computation . they propose 'coldfusion' can create synergistic loop where finetuned models can be "recycled" |
| Outcome: | The proposed method outperforms RoBERTa and previous multitask models on 35 datasets. |