9 citations · 17 across the 9 of their papers we have counts for
9 papers
What Makes the Story Forward? Inferring Commonsense Explanations as Prompts for Future Event Generation
Li Lin, Yixin Cao, Lifu Huang +4
Prediction over event sequences is critical for many real-world applications in Information Retrieval and Natural Language Processing. Future Event Generation (FEG) is a challengin…
Learning Algebraic Recombination for Compositional Generalization
Chenyao Liu, Shengnan An, Zeqi Lin +6
Neural sequence models exhibit limited compositional generalization ability in semantic parsing tasks. Compositional generalization requires algebraic recombination, i.e., dynamica…
GAHNE: Graph-Aggregated Heterogeneous Network Embedding
Xiaohe Li, Lijie Wen, Chen Qian +1
The real-world networks often compose of different types of nodes and edges with rich semantics, widely known as heterogeneous information network (HIN). Heterogeneous network embe…
Semi-supervised Relation Extraction via Incremental Meta Self-Training
Xuming Hu, Chenwei Zhang, Fukun Ma +3
To alleviate human efforts from obtaining large-scale annotations, Semi-Supervised Relation Extraction methods aim to leverage unlabeled data in addition to learning from limited s…
SelfORE: Self-supervised Relational Feature Learning for Open Relation Extraction
Xuming Hu, Chenwei Zhang, Yusong Xu +2
Open relation extraction is the task of extracting open-domain relation facts from natural language sentences. Existing works either utilize heuristics or distant-supervised annota…
An Approach for Process Model Extraction By Multi-Grained Text Classification
Chen Qian, Lijie Wen, Akhil Kumar +5
Process model extraction (PME) is a recently emerged interdiscipline between natural language processing (NLP) and business process management (BPM), which aims to extract process…
TraceWalk: Semantic-based Process Graph Embedding for Consistency Checking
Chen Qian, Lijie Wen, Akhil Kumar
Process consistency checking (PCC), an interdiscipline of natural language processing (NLP) and business process management (BPM), aims to quantify the degree of (in)consistencies…
BePT: A Behavior-based Process Translator for Interpreting and Understanding Process Models
Chen Qian, Lijie Wen, Akhil Kumar
Sharing process models on the web has emerged as a common practice. Users can collect and share their experimental process models with others. However, some users always feel confu…
Computation of Transition Adjacency Relations Based on Complete Prefix Unfolding (Technical Report)
Jisheng Pei, Lijie Wen, Akhil Kumar +1
An increasing number of works have devoted to the application of Transition Adjacency Relation (TAR) as a means to capture behavioral features of business process models. In this p…