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Found 6 papers, 2 papers with code
Wiki-LLaVA: Hierarchical Retrieval-Augmented Generation for Multimodal LLMs
Multimodal LLMs are the natural evolution of LLMs, and enlarge their capabilities so as to work beyond the pure textual modality.
The (R)Evolution of Multimodal Large Language Models: A Survey
Connecting text and visual modalities plays an essential role in generative intelligence.
With a Little Help from your own Past: Prototypical Memory Networks for Image Captioning
Image captioning, like many tasks involving vision and language, currently relies on Transformer-based architectures for extracting the semantics in an image and translating it into linguistically coherent descriptions.
Multi-Class Explainable Unlearning for Image Classification via Weight Filtering
Machine Unlearning has recently been emerging as a paradigm for selectively removing the impact of training datapoints from a network.
Positive-Augmented Contrastive Learning for Image and Video Captioning Evaluation
The CLIP model has been recently proven to be very effective for a variety of cross-modal tasks, including the evaluation of captions generated from vision-and-language architectures.
Retrieval-Augmented Transformer for Image Captioning
In this paper, we investigate the development of an image captioning approach with a kNN memory, with which knowledge can be retrieved from an external corpus to aid the generation process.
