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Found 5 papers, 3 papers with code
A Probabilistic Framework for Lifelong Test-Time Adaptation
Test-time adaptation (TTA) is the problem of updating a pre-trained source model at inference time given test input(s) from a different target domain.
Hypernetworks for Continual Semi-Supervised Learning
Further, we present $\textit{Semi-Split CIFAR-10}$, a new benchmark for continual semi-supervised learning, obtained by modifying the $\textit{Split CIFAR-10}$ dataset, in which the tasks with labelled and unlabelled data arrive sequentially.
Fine-Grained Emotion Prediction by Modeling Emotion Definitions
In this paper, we propose a new framework for fine-grained emotion prediction in the text through emotion definition modeling.
Deep Attentive Ranking Networks for Learning to Order Sentences
We apply our framework on two tasks: Sentence Ordering and Order Discrimination.
A Meta-Learning Framework for Generalized Zero-Shot Learning
Our proposed model yields significant improvements on standard ZSL as well as more challenging GZSL setting.
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