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Found 8 papers, 3 papers with code
Benchmarking Meaning Representations in Neural Semantic Parsing
Thus, the impact of meaning representation on semantic parsing is less understood.
Few-Sample Named Entity Recognition for Security Vulnerability Reports by Fine-Tuning Pre-Trained Language Models
In this work, for the first time, we propose to investigate this problem where only a small number of labeled training samples are available.
An Empirical Study on Hyperparameter Optimization for Fine-Tuning Pre-trained Language Models
We find that using the same time budget, HPO often fails to outperform grid search due to two reasons: insufficient time budget and overfitting.
Latent neural source recovery via transcoding of simultaneous EEG-fMRI
Simultaneous EEG-fMRI is a multi-modal neuroimaging technique that provides complementary spatial and temporal resolution for inferring a latent source space of neural activity.
Deep Neural Networks with Koopman Operators for Modeling and Control of Autonomous Vehicles
Furthermore, a data-driven model predictive controller with the learned Koopman model is designed for path tracking control of autonomous vehicles.
Unsupervised Sparse-view Backprojection via Convolutional and Spatial Transformer Networks
Many imaging technologies rely on tomographic reconstruction, which requires solving a multidimensional inverse problem given a finite number of projections.
Substituting Gadolinium in Brain MRI Using DeepContrast
Together, these studies validate our hypothesis that a deep learning approach can potentially replace the need for GBCAs in brain MRI.
Scalable and Robust Construction of Topical Hierarchies
Automated generation of high-quality topical hierarchies for a text collection is a dream problem in knowledge engineering with many valuable applications.