27 citations · 132 across the 66 of their papers we have counts for
5 papers · 1 filter
Semi-Supervised Disentangled Framework for Transferable Named Entity Recognition
Zhifeng Hao, Di Lv, Zijian Li +3
Named entity recognition (NER) for identifying proper nouns in unstructured text is one of the most important and fundamental tasks in natural language processing. However, despite…
Time Series Domain Adaptation via Sparse Associative Structure Alignment
Ruichu Cai, Jiawei Chen, Zijian Li +6
Domain adaptation on time series data is an important but challenging task. Most of the existing works in this area are based on the learning of the domain-invariant representation…
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs
Feng Xie, Ruichu Cai, Biwei Huang +3
Causal discovery aims to recover causal structures or models underlying the observed data. Despite its success in certain domains, most existing methods focus on causal relations b…
Causal Discovery with Multi-Domain LiNGAM for Latent Factors
Yan Zeng, Shohei Shimizu, Ruichu Cai +3
Discovering causal structures among latent factors from observed data is a particularly challenging problem. Despite some efforts for this problem, existing methods focus on the si…
TAG : Type Auxiliary Guiding for Code Comment Generation
Ruichu Cai, Zhihao Liang, Boyan Xu +3
Existing leading code comment generation approaches with the structure-to-sequence framework ignores the type information of the interpretation of the code, e.g., operator, string,…