标签:Learning arxiv Machine abs Survey https Paper org
A Survey on Making Deep Learning Models Smaller, Faster, and Better
https://arxiv.org/abs/2106.08962
Decoding-Time Controlled Text Generation with Experts and Anti-Experts
https://arxiv.org/abs/2105.03023
https://github.com/alisawuffles/DExperts
Graph Neural Networks for Natural Language Processing: A Survey
https://arxiv.org/abs/2106.06090
A Survey of Transformers
https://arxiv.org/abs/2106.04554
Pretrained Language Models for Text Generation: A Survey
https://arxiv.org/abs/2105.10311
A Survey of Data Augmentation Approaches for NLP
https://arxiv.org/abs/2105.03075
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
https://arxiv.org/abs/2104.13478
The NLP Cookbook: Modern Recipes for Transformer based Deep Learning Architectures
https://arxiv.org/abs/2104.10640
A Practical Survey on Faster and Lighter Transformers
https://arxiv.org/abs/2103.14636
Requirement Engineering Challenges for AI-intense Systems Development
https://arxiv.org/abs/2103.10270
Model Complexity of Deep Learning: A Survey
https://arxiv.org/abs/2103.05127
A Survey on Visual Transformer
https://arxiv.org/abs/2012.12556
A Comprehensive Survey on Graph Neural Networks
https://arxiv.org/abs/1901.00596
标签:Learning,arxiv,Machine,abs,Survey,https,Paper,org 来源: https://www.cnblogs.com/songyuejie/p/14912661.html
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