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Found 12 papers, 3 papers with code
Automatic Keyphrase Generation by Incorporating Dual Copy Mechanisms in Sequence-to-Sequence Learning
However, we observed that most of the keyphrases are composed of some important words (seed words) in the source text, and if these words can be identified accurately and copied to create more keyphrases, the performance of the model might be improved.
Omniview-Tuning: Boosting Viewpoint Invariance of Vision-Language Pre-training Models
Vision-Language Pre-training (VLP) models like CLIP have achieved remarkable success in computer vision and particularly demonstrated superior robustness to distribution shifts of 2D images.
Embodied Adversarial Attack: A Dynamic Robust Physical Attack in Autonomous Driving
As physical adversarial attacks become extensively applied in unearthing the potential risk of security-critical scenarios, especially in autonomous driving, their vulnerability to environmental changes has also been brought to light.
Towards Transferable Targeted 3D Adversarial Attack in the Physical World
However, the field of transferable targeted 3D adversarial attacks remains vacant.
Unified Adversarial Patch for Visible-Infrared Cross-modal Attacks in the Physical World
We also demonstrate the effectiveness of our approach in physical-world scenarios under various settings, including different angles, distances, postures, and scenes for both visible and infrared sensors.
Unified Adversarial Patch for Cross-modal Attacks in the Physical World
To show the potential risks under such scenes, we propose a unified adversarial patch to perform cross-modal physical attacks, i. e., fooling visible and infrared object detectors at the same time via a single patch.
HOSSnet: an Efficient Physics-Guided Neural Network for Simulating Crack Propagation
Hybrid Optimization Software Suite (HOSS), which is a combined finite-discrete element method (FDEM), is one of the advanced approaches to simulating high-fidelity fracture and fragmentation processes but the application of pure HOSS simulation is computationally expensive.
Few-shot Medical Image Segmentation via Cross-Reference Transformer
We first enhance the correlation features between the support set image and the query image using a bidirectional cross-attention module.
Continual Graph Convolutional Network for Text Classification
Graph convolutional network (GCN) has been successfully applied to capture global non-consecutive and long-distance semantic information for text classification.
HomPINNs: homotopy physics-informed neural networks for solving the inverse problems of nonlinear differential equations with multiple solutions
Due to the complex behavior arising from non-uniqueness, symmetry, and bifurcations in the solution space, solving inverse problems of nonlinear differential equations (DEs) with multiple solutions is a challenging task.
Machine unlearning via GAN
Machine learning models, especially deep models, may unintentionally remember information about their training data.
Lightweight machine unlearning in neural network
Our method only needs to make a small perturbation of the weight of the target model and make it iterate in the direction of the model trained with the remaining data subset until the contribution of the unlearning data to the model is completely eliminated.
