Papers with few-shot domain adaptation setting
Retrieving Multimodal Prompts for Generative Visual Question Answering (2023.findings-acl)
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| Challenge: | Visual question answering (VQA) is a multimodal machine learning problem that challenges a model to answer a question posed about an image. |
| Approach: | They propose a generative model enhanced by multimodal prompt retrieval that integrates retrieved prompts and multimodal features to generate answers in free text. |
| Outcome: | The proposed model outperforms its non-retrieval counterpart by 30% on medical VQA tasks. |
CORE: A Few-Shot Company Relation Classification Dataset for Robust Domain Adaptation. (2023.emnlp-main)
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| Challenge: | Existing datasets that focus on company relations and business entities are lacking in relation classification. |
| Approach: | They introduce a few-shot relation classification dataset for company relations and business entities . they use a dataset that includes 4,708 instances of 12 relation types . |
| Outcome: | The proposed dataset includes 4,708 instances of 12 relation types with corresponding textual evidence extracted from company Wikipedia pages. |