Self-Attention with State-Object Weighted Combination for Compositional Zero Shot Learning

This article announces a research paper on a novel approach to compositional zero-shot learning. The core idea involves using self-attention with a weighted combination of state and object representations. The focus is on improving the model's ability to generalize to unseen combinations of concepts. The source is ArXiv, indicating a pre-print and peer review is likely pending.