Search Results for author:
Found 6 papers, 4 papers with code
Diffeomorphism Neural Operator for various domains and parameters of partial differential equations
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).
MC^2: A Multilingual Corpus of Minority Languages in China
However, existing LLMs exhibit limited abilities in understanding low-resource languages, including the minority languages in China, due to a lack of training data.
Contrastive Learning for Predicting Cancer Prognosis Using Gene Expression Values
Using data from The Cancer Genome Atlas (TCGA), we demonstrated that our CL-based Cox model (CLCox) significantly outperformed existing methods in predicting the prognosis of 19 types of cancer considered.
From the One, Judge of the Whole: Typed Entailment Graph Construction with Predicate Generation
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.
Lawyer LLaMA Technical Report
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.
Entailment Graph Learning with Textual Entailment and Soft Transitivity
Typed entailment graphs try to learn the entailment relations between predicates from text and model them as edges between predicate nodes.
