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Found 3 papers, 3 papers with code
LMCap: Few-shot Multilingual Image Captioning by Retrieval Augmented Language Model Prompting
Multilingual image captioning has recently been tackled by training with large-scale machine translated data, which is an expensive, noisy, and time-consuming process.
Retrieval-augmented Image Captioning
The encoder in our model jointly processes the image and retrieved captions using a pretrained V&L BERT, while the decoder attends to the multimodal encoder representations, benefiting from the extra textual evidence from the retrieved captions.
SmallCap: Lightweight Image Captioning Prompted with Retrieval Augmentation
Recent advances in image captioning have focused on scaling the data and model size, substantially increasing the cost of pre-training and finetuning.
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