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Decomposed soft prompt guided fusion enhancing for compositional zero-shot learning
Abstract Compositional Zero-Shot Learning (CZSL) aims to recognize novel concepts
formed by known states and objects during training. Existing methods either learn the …
formed by known states and objects during training. Existing methods either learn the …
Data distribution distilled generative model for generalized zero-shot recognition
In the realm of Zero-Shot Learning (ZSL), we address biases in Generalized Zero-Shot
Learning (GZSL) models, which favor seen data. To counter this, we introduce an end-to …
Learning (GZSL) models, which favor seen data. To counter this, we introduce an end-to …
[PDF][PDF] Parsnets: A parsimonious composition of orthogonal and low-rank linear networks for zero-shot learning
This paper provides a novel parsimonious yet efficient design for zero-shot learning (ZSL),
dubbed ParsNets, in which we are interested in learning a composition of on-device friendly …
dubbed ParsNets, in which we are interested in learning a composition of on-device friendly …
Mdenet: multi-modal dual-embedding networks for malware open-set recognition
Malware open-set recognition (MOSR) aims at jointly classifying malware samples from
known families and detect the ones from novel unknown families, respectively. Existing …
known families and detect the ones from novel unknown families, respectively. Existing …