2023 - Research.com Rising Star of Science Award
2022 - Research.com Rising Star of Science Award
Artificial intelligence, Natural language processing, Information retrieval, Machine learning and Text corpus are his primary areas of study. His work often combines Artificial intelligence and Context studies. He works in the field of Natural language processing, namely Text mining.
The study incorporates disciplines such as Bayesian probability and Social network in addition to Information retrieval. His Machine learning research incorporates elements of Named-entity recognition and Sequence labeling. Knowledge-based systems, Taxonomy, Topic model and Object is closely connected to Information extraction in his research, which is encompassed under the umbrella topic of Text corpus.
Xiang Ren focuses on Artificial intelligence, Natural language processing, Machine learning, Text corpus and Relationship extraction. In his works, Xiang Ren performs multidisciplinary study on Artificial intelligence and Context. His work on Sentence, Question answering, Phrase and Parsing as part of general Natural language processing research is frequently linked to Synonym, thereby connecting diverse disciplines of science.
Xiang Ren combines subjects such as Embedding and Sequence labeling with his study of Machine learning. His Text corpus research includes elements of Knowledge base, Text mining, Knowledge extraction, Social media and String. His study in Relationship extraction is interdisciplinary in nature, drawing from both Sentiment analysis, Labeled data, Training set and Leverage.
His primary areas of investigation include Artificial intelligence, Natural language processing, Language model, Machine learning and Question answering. Reinforcement learning, Transformer, Benchmark, Transfer of learning and Automatic summarization are the core of his Artificial intelligence study. His Natural language processing research focuses on Commonsense reasoning and how it connects with Generative grammar.
His research integrates issues of Natural language understanding, Commonsense knowledge and Set in his study of Language model. His Machine learning research focuses on subjects like Inference, which are linked to Robustness. Xiang Ren focuses mostly in the field of Question answering, narrowing it down to matters related to Knowledge graph and, in some cases, Graph, Theoretical computer science and Interpretability.
Xiang Ren mostly deals with Artificial intelligence, Natural language processing, Language model, Machine learning and Sentence. His study in Artificial intelligence concentrates on Benchmark, Natural language, Sequence labeling, Annotation and False positive paradox. His research in Natural language processing intersects with topics in Semantics, Construct and Named-entity recognition.
His Language model study also includes fields such as
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Hierarchical graph representation learning with differentiable pooling
Zhitao Ying;Jiaxuan You;Christopher Morris;Xiang Ren.
neural information processing systems (2018)
Personalized entity recommendation: a heterogeneous information network approach
Xiao Yu;Xiang Ren;Yizhou Sun;Quanquan Gu.
web search and data mining (2014)
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
Jiaxuan You;Rex Ying;Xiang Ren;William L. Hamilton.
international conference on machine learning (2018)
Dynamic Network Embedding by Modeling Triadic Closure Process.
Le-kui Zhou;Yang Yang;Xiang Ren;Fei Wu.
national conference on artificial intelligence (2018)
Empower Sequence Labeling with Task-Aware Neural Language Model
Liyuan Liu;Jingbo Shang;Frank F. Xu;Xiang Ren.
national conference on artificial intelligence (2017)
Automated Phrase Mining from Massive Text Corpora
Jingbo Shang;Jialu Liu;Meng Jiang;Xiang Ren.
IEEE Transactions on Knowledge and Data Engineering (2018)
CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases
Xiang Ren;Zeqiu Wu;Wenqi He;Meng Qu.
the web conference (2017)
Mining Quality Phrases from Massive Text Corpora
Jialu Liu;Jingbo Shang;Chi Wang;Xiang Ren.
international conference on management of data (2015)
KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning
Bill Yuchen Lin;Xinyue Chen;Jamin Chen;Xiang Ren.
empirical methods in natural language processing (2019)
Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning
Xuan Wang;Yu Zhang;Xiang Ren;Yuhao Zhang.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: