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Found 5 papers, 3 papers with code
PanGu-$π$: Enhancing Language Model Architectures via Nonlinearity Compensation
We then demonstrate that the proposed approach is significantly effective for enhancing the model nonlinearity through carefully designed ablations; thus, we present a new efficient model architecture for establishing modern, namely, PanGu-$\pi$.
Digital Twin-based Anomaly Detection with Curriculum Learning in Cyber-physical Systems
LATTICE also, on average, reduces the training time of ATTAIN by 4. 2% on the five datasets and is on par with the baselines in terms of detection delay time.
Knowledge Distillation-Empowered Digital Twin for Anomaly Detection
However, constructing a DT for anomaly detection in TCMS necessitates sufficient training data and extracting both chronological and context features with high quality.
EvoCLINICAL: Evolving Cyber-Cyber Digital Twin with Active Transfer Learning for Automated Cancer Registry System
To tackle this challenge, we propose EvoCLINICAL, which considers the CCDT developed for the previous version of GURI as the pretrained model and fine-tunes it with the dataset labelled by querying a new GURI version.
An Encoding Strategy Based Word-Character LSTM for Chinese NER
A recently proposed lattice model has demonstrated that words in character sequence can provide rich word boundary information for character-based Chinese NER model.
