NLP Data Augmentation Techniques 1. Lexical Substitution This line of work tries to substitute words present in a text without changing the meaning of the sentence. a. Thesaurus-based substitution In this techn
📙 A Visual Survey of Data Augmentation in NLP [Blog, 2020] 📙 Weak Supervision: A New Programming Paradigm for Machine Learning [Blog, March 2019] Named Entity Recognition (NER) ⭐ Datasets for Entity Recognition [GitHub, 1497 stars] ⭐ Datasets to train supervised classifiers for Named...
由于这类手动注释的数据集永远不足以学习高质量的模型,早期的NLP模型在很大程度上依赖于特征工程(表1(a);例如,Guyon等(2002),Lafferty等(2001),Och等(2004),Zhang和Nivre(2011)),NLP研究人员或工程师利用他们的领域知识从原始数据中定义和提取显著特征,并为模型提供适当的归纳偏差,以从这些有限的数据中学习。随着...
A project associated with this survey has been built at https://github.com/xiaoaoran/3D_label_efficient_learning.Index Terms: Point cloud, label-efficient learning, data augmentation, semi-supervised learning, weakly-supervised learning, few-shot learning, domain adaptation, domain generalization, ...
Vid2seq: Large-scale pretraining of a visual language model for dense video captioning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 10714–10726, 2023. [Yang等人,2023b] Haoyan Yang, Zhitao Li, Yong Zhang, Jianzong Wang, Ning Cheng, Ming Li,...
A Survey of Surveys (NLP & ML) In this document, we survey hundreds of survey papers on Natural Language Processing (NLP) and Machine Learning (ML). We categorize these papers into popular topics and do simple counting for some interesting problems. In addition, we show the list of the pa...
2. Modalities in smart healthcare 3. SOTA techniques in multimodal fusion for smart healthcare 4. Challenges in adopting multimodal fusion 5. DIKW fusion framework with multimodality 6. Future directions of DIKW fusion in smart healthcare 7. Conclusion CRediT authorship contribution statement Declaratio...
An ANN usually involves manyprocessorsoperating in parallel and arranged in tiers or layers. There are typically three layers in a neural network: an input layer, an output layer and several hidden layers. The first tier -- analogous to optic nerves in human visual processing -- receives the ...
Consequently, when applied to medical domains beyond the training data, their effectiveness diminishes. The prompt learning method presents a novel approach for enhancing the performance of few-shot learning in NLP tasks. This method involves encapsulating the input sentence within a natural language ...
The leading approaches in Machine Learning are notoriously data-hungry. Unfortunately, many application domains do not have access to big data because acquiring data involves a process that is expensive or time-consuming. This has triggered a serious deb