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Found 6 papers, 1 papers with code
Large Language Models in the Clinic: A Comprehensive Benchmark
The adoption of large language models (LLMs) to assist clinicians has attracted remarkable attention.
Feature Aggregation Network for Building Extraction from High-resolution Remote Sensing Images
In this work, we propose the Feature Aggregation Network (FANet), concentrating on extracting both global and local features, thereby enabling the refined extraction of landmark buildings from high-resolution satellite remote sensing imagery.
FLDNet: A Foreground-Aware Network for Polyp Segmentation Leveraging Long-Distance Dependencies
On the high-level features, the local context module obtains the local characteristics related to the polyps by constructing different local context information.
A Fuzzy-set-based Joint Distribution Adaptation Method for Regression and its Application to Online Damage Quantification for Structural Digital Twin
Thanks to the superiority of the proposed method, a state-of-the-art online damage quantification framework based on domain adaptation is presented.
Multi-Grained Knowledge Distillation for Named Entity Recognition
To maximally assimilate knowledge into the student model, we propose a multi-grained distillation scheme, which integrates cross entropy involved in conditional random field (CRF) and fuzzy learning. To validate the effectiveness of our proposal, we conducted a comprehensive evaluation on five NER benchmarks, reporting cross-the-board performance gains relative to competing prior-arts.
Deep Reinforcement Learning in a Monetary Model
We propose using deep reinforcement learning to solve dynamic stochastic general equilibrium models.
