MetaReVision: Meta-Learning with Retrieval for Visually Grounded Compositional Concept Acquisition (2023.findings-emnlp)
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| Challenge: | Existing methods to learn compositional concepts from previous experience are based on systematic generalization, productivity and substitutivity. |
| Approach: | They propose a retrieval-enhanced meta-learning model to solve the visually grounded compositional concept learning problem by meta-training retrieved primitive concepts from episodes constructed by the retriever. |
| Outcome: | The proposed model outperforms other baselines and the retrieval module plays an important role in this compositional learning process. |
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