Towards Practical Few-shot Federated NLP

Transformer-based pre-trained models have emerged as the predominant solution for natural language processing (NLP). Fine-tuning such pre-trained models for downstream tasks often requires a considerable amount of labeled private data. In practice, private data is often distributed across heterogeneous mobile devices and may be prohibited from being uploaded. Moreover, well-curated labeled data is often scarce, presenting an additional challenge. To address these challenges, we first introduce a data generator for federated few-shot learning tasks, which encompasses the quantity and skewness of scarce labeled data in a realistic setting. Subsequently, we propose AUG-FedPrompt, a prompt-based federated learning system that exploits abundant unlabeled data for data augmentation. Our experiments indicate that AUG-FedPrompt can perform on par with full-set fine-tuning with a limited amount of labeled data. However, such competitive performance comes at a significant system cost.Comment: EuroSys23 worksho

Characteristics, hotspots, and prospects of short video research: A review of papers published in China from 2012 to 2022

In recent years, due to the increase in their global popularity, short video applications have become an important topic of research. The number of users has now exceeded one billion in China; accordingly, Chinese researchers have conducted many studies on short videos. Their findings can serve as important references for both theoretical research on and the practical development of short videos worldwide. In this study, we used bibliometrics method and the CiteSpace application to analyze the content of 2163 representative research papers on short videos published in China from 2012 to 2022. The number of such papers is increasing annually in China; moreover, several core groups of authors and research institutions focusing on short video research have already been formed. Some popular topics of research on these videos include the main characteristics of short videos, phenomenon of media convergence based on short videos, and application scenarios of short videos. Over the years, research on the popular short video application Douyin has been increasing, as well. The research results indicate that issues such as the marketing of short knowledge videos, standardized management of short video platforms, and impact of these videos on the education of college students are expected to become popular subjects of scholarly research in the near future

Mesalazine Modified-Release Tablet in the Treatment of Ulcerative Colitis in the Active Phase: A Chinese, Multicenter, Single-Blind, Randomized Controlled Study

<p><b>Article full text</b></p><p><br></p><p>The full text of this article can be found <a href="https://link.springer.com/article/10.1007/s12325-016-0303-z"><b>here</b>.</a></p><p><br></p><p><b>Provide enhanced content for this article</b></p><p><br></p><p>If you are an author of this publication and would like to provide additional enhanced content for your article then please contact <a href="http://www.medengine.com/Redeem/”mailto:[email protected]”"><b>[email protected]</b></a>.</p><p> </p><p>The journal offers a range of additional features designed to increase visibility and readership. All features will be thoroughly peer reviewed to ensure the content is of the highest scientific standard and all features are marked as ‘peer reviewed’ to ensure readers are aware that the content has been reviewed to the same level as the articles they are being presented alongside. Moreover, all sponsorship and disclosure information is included to provide complete transparency and adherence to good publication practices. This ensures that however the content is reached the reader has a full understanding of its origin. No fees are charged for hosting additional open access content.</p><p><br></p><p>Other enhanced features include, but are not limited to:</p><p><br></p><p>• Slide decks</p><p>• Videos and animations</p><p>• Audio abstracts</p><p> • Audio slides<br></p

Robotic Grasp Detection Network Based on Improved Deformable Convolution and Spatial Feature Center Mechanism

In this article, we propose an effective grasp detection network based on an improved deformable convolution and spatial feature center mechanism (DCSFC-Grasp) to precisely grasp unidentified objects. DCSFC-Grasp includes three key procedures as follows. First, improved deformable convolution is introduced to adaptively adjust receptive fields for multiscale feature information extraction. Then, an efficient spatial feature center (SFC) layer is explored to capture the global remote dependencies through a lightweight multilayer perceptron (MLP) architecture. Furthermore, a learnable feature center (LFC) mechanism is reported to gather local regional features and preserve the local corner region. Finally, a lightweight CARAFE operator is developed to upsample the features. Experimental results show that DCSFC-Grasp achieves a high accuracy (99.3% and 96.1% for the Cornell and Jacquard grasp datasets, respectively) and even outperforms the existing state-of-the-art grasp detection models. The results of real-world experiments on the six-DoF Realman RM65 robotic arm further demonstrate that our DCSFC-Grasp is effective and robust for the grasping of unknown targets