Class Specific Feature Disentanglement and Text Embeddings for Multi-label Generalized Zero Shot CXR Classification

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Publications associées (31)

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Abstractive summarization has seen big improvements in recent years, mostly due to advances in neural language modeling, language model pretraining, and scaling models and datasets. While large language models generate summaries that are fluent, coherent, ...

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The way biological brains carry out advanced yet extremely energy efficient signal processing remains both fascinating and unintelligible. It is known however that at least some areas of the brain perform fast and low-cost processing relying only on a smal ...

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Single Domain Generalization (SDG) tackles the problem of training a model on a single source domain so that it generalizes to any unseen target domain. While this has been well studied for image classification, the literature on SDG object detection remai ...

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Estimating and Improving the Robustness of Attributions in Text

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End-to-end learning methods like deep neural networks have been the driving force in the remarkable progress of machine learning in recent years. However, despite their success, the deployment process of such networks in safety-critical use cases, such as ...

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Effect of wettability and textile architecture on fluid displacement and pore formation during infiltration of carbon fibrous preforms

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We seek to address how air entrapment mechanisms during infiltration are influenced by the wetting characteristics of the fluid and the pore network formed by the reinforcement. To this end, we evaluated the behavior of two model fluids with different surf ...

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Segmenting Without Annotating: Crack Segmentation and Monitoring via Post-Hoc Classifier Explanations

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Monitoring the cracks in walls, roads and other types of infrastructure is essential to ensure the safety of a structure, and plays an important role in structural health monitoring. Automatic visual inspection allows an efficient, costeffective and safe h ...

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