Papers with MetaReVision

1 papers
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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