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Found 6 papers, 1 papers with code
`Eyes of a Hawk and Ears of a Fox': Part Prototype Network for Generalized Zero-Shot Learning
Current approaches in Generalized Zero-Shot Learning (GZSL) are built upon base models which consider only a single class attribute vector representation over the entire image.
CREPE: Learnable Prompting With CLIP Improves Visual Relationship Prediction
In this paper, we explore the potential of Vision-Language Models (VLMs), specifically CLIP, in predicting visual object relationships, which involves interpreting visual features from images into language-based relations.
Transfer Learning in Visual and Relational Reasoning
Transfer learning has become the de facto standard in computer vision and natural language processing, especially where labeled data is scarce.
On transfer learning using a MAC model variant
We introduce a variant of the MAC model (Hudson and Manning, ICLR 2018) with a simplified set of equations that achieves comparable accuracy, while training faster.
Using Multi-task and Transfer Learning to Solve Working Memory Tasks
We propose a new architecture called Memory-Augmented Encoder-Solver (MAES) that enables transfer learning to solve complex working memory tasks adapted from cognitive psychology.
Learning to Remember, Forget and Ignore using Attention Control in Memory
Typical neural networks with external memory do not effectively separate capacity for episodic and working memory as is required for reasoning in humans.
