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20152022
most citedSelfORE: Self-supervised Relational Feature Learning for Open Relation Extraction

9 citations · 17 across the 9 of their papers we have counts for

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Showing cs.CLShow all

6 papers · 1 filter

cs.CL2022★ 1 cited

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…

cs.CL2021

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…

cs.CL2020★ 2 cited

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…

cs.CL2020★ 9 cited

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…

cs.CL2019

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…

cs.CL2019★ 2 cited

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…