Papers by Oscar Mañas
MAPL: Parameter-Efficient Adaptation of Unimodal Pre-Trained Models for Vision-Language Few-Shot Prompting (2023.eacl-main)
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| Challenge: | Large pre-trained models have proved to be remarkable zero- and (prompt-based) few-shot learners in unimodal vision and language tasks. |
| Approach: | They propose to use frozen unimodal models to learn a lightweight mapping between the representation spaces of unimod models using aligned image-text data. |
| Outcome: | The proposed method can generalize to unseen VL tasks from a few in-context examples while training orders of magnitude fewer parameters. |