no code implementations • 19 Feb 2024 • Zhiwei Zhao, Changqing Liu, Yingguang Li, Zhibin Chen, Xu Liu
Neural operator models provide an efficient alternative by learning the governing physical laws directly from data in a class of PDEs with different parameters, but constrained in a fixed boundary (domain).
1 code implementation • 14 Nov 2023 • Chen Zhang, Mingxu Tao, Quzhe Huang, Jiuheng Lin, Zhibin Chen, Yansong Feng
However, existing LLMs exhibit limited abilities in understanding low-resource languages, including the minority languages in China, due to a lack of training data.
1 code implementation • 9 Jun 2023 • Anchen Sun, Elizabeth J. Franzmann, Zhibin Chen, Xiaodong Cai
CL-based classifiers and CLCox models for 19 types of cancer are publicly available and can be used to predict cancer prognosis using the RNA-seq transcriptome of an individual tumor.
1 code implementation • 7 Jun 2023 • Zhibin Chen, Yansong Feng, Dongyan Zhao
Entailment Graphs (EGs) have been constructed based on extracted corpora as a strong and explainable form to indicate context-independent entailment relations in natural languages.
1 code implementation • 24 May 2023 • Quzhe Huang, Mingxu Tao, Chen Zhang, Zhenwei An, Cong Jiang, Zhibin Chen, Zirui Wu, Yansong Feng
Specifically, we inject domain knowledge during the continual training stage and teach the model to learn professional skills using properly designed supervised fine-tuning tasks.
1 code implementation • ACL 2022 • Zhibin Chen, Yansong Feng, Dongyan Zhao
Typed entailment graphs try to learn the entailment relations between predicates from text and model them as edges between predicate nodes.