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Found 12 papers, 8 papers with code
MedDialog: Large-scale Medical Dialogue Datasets
We also study the transferability of models trained on MedDialog to low-resource medical dialogue generation tasks.
A Survey on Cross-Domain Sequential Recommendation
Cross-domain sequential recommendation (CDSR) shifts the modeling of user preferences from flat to stereoscopic by integrating and learning interaction information from multiple domains at different granularities (ranging from inter-sequence to intra-sequence and from single-domain to cross-domain).
Siamese Representation Learning for Unsupervised Relation Extraction
Unsupervised relation extraction (URE) aims at discovering underlying relations between named entity pairs from open-domain plain text without prior information on relational distribution.
SAM-Deblur: Let Segment Anything Boost Image Deblurring
Image deblurring is a critical task in the field of image restoration, aiming to eliminate blurring artifacts.
Improving Neural Radiance Fields with Depth-aware Optimization for Novel View Synthesis
Through these explicit constraints and the implicit constraint from NeRF, our method improves the view synthesis as well as the 3D-scene geometry performance of NeRF at the same time.
Structure-Aware NeRF without Posed Camera via Epipolar Constraint
This two-stage strategy is not convenient to use and degrades the performance because the error in the pose extraction can propagate to the view synthesis.
On the Generation of Medical Dialogs for COVID-19
Training complex dialog generation models on small datasets bears high risk of overfitting.
Estimation of 3D Human Pose Using Prior Knowledge
Estimating three-dimensional human poses from the positions of two-dimensional joints has shown promising results. However, using two-dimensional joint coordinates as input loses more information than image-based approaches and results in ambiguity. In order to overcome this problem, we combine bone length and camera parameters with two-dimensional joint coordinates for input. This combination is more discriminative than the two-dimensional joint coordinates in that it can improve the accuracy of the model's prediction depth and alleviate the ambiguity that comes from projecting three-dimensional coordinates into two-dimensional space.
Dynamical evolution in a one-dimensional incommensurate lattice with $\mathcal{PT}$ symmetry
We investigate the dynamical evolution of a parity-time ($\mathcal{PT}$) symmetric extension of the Aubry-Andr\'{e} (AA) model, which exhibits the coincidence of a localization-delocalization transition point with a $\mathcal{PT}$ symmetry breaking point.
Disordered Systems and Neural Networks
On the Generation of Medical Dialogues for COVID-19
On these two datasets, we train several dialogue generation models based on Transformer, GPT, and BERT-GPT.
MedDialog: Two Large-scale Medical Dialogue Datasets
Medical dialogue systems are promising in assisting in telemedicine to increase access to healthcare services, improve the quality of patient care, and reduce medical costs.
Real-Time Illegal Parking Detection System Based on Deep Learning
Experiments show that the system can achieve a 99% accuracy and real-time (25FPS) detection with strong robustness in complex environments.
