Controlling the Focus of Pretrained Language Generation Models (2022.findings-acl)
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| Challenge: | Existing mechanisms to control the model's focus are not available for pretrained transformer-based language generation models. |
| Approach: | They propose to augment a pretrained model with trainable "focus vectors" that are directly applied to the model's embeddings while the model itself is kept fixed. |
| Outcome: | The proposed model is able to generate relevant outputs from user-selected highlights while keeping the model fixed. |
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Manuel Mager, Ramón Fernandez Astudillo, Tahira Naseem, Md Arafat Sultan, Young-Suk Lee, Radu Florian, Salim Roukos
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