22 citations · 52 across the 3 of their papers we have counts for
4 papers
CPM-2: Large-scale Cost-effective Pre-trained Language Models
Zhengyan Zhang, Yuxian Gu, Xu Han +16
In recent years, the size of pre-trained language models (PLMs) has grown by leaps and bounds. However, efficiency issues of these large-scale PLMs limit their utilization in real-…
Pre-Trained Models: Past, Present and Future
Xu Han, Zhengyan Zhang, Ning Ding +21
Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved great success and become a milestone in the field of artificial intelligence (AI). Owing to sophis…
CPM: A Large-scale Generative Chinese Pre-trained Language Model
Zhengyan Zhang, Xu Han, Hao Zhou +22
Pre-trained Language Models (PLMs) have proven to be beneficial for various downstream NLP tasks. Recently, GPT-3, with 175 billion parameters and 570GB training data, drew a lot o…
CyLKs: Unsupervised Cycle Lucas-Kanade Network for Landmark Tracking
Xinshuo Weng, Wentao Han
Across a majority of modern learning-based tracking systems, expensive annotations are needed to achieve state-of-the-art performance. In contrast, the Lucas-Kanade (LK) algorithm…