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20192022
most citedGeneralizing from a Few Examples: A Survey on Few-Shot Learning

791 citations · 963 across the 16 of their papers we have counts for

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cs.CL2021

Hierarchical Heterogeneous Graph Representation Learning for Short Text Classification

Yaqing Wang, Song Wang, Quanming Yao +1

Short text classification is a fundamental task in natural language processing. It is hard due to the lack of context information and labeled data in practice. In this paper, we pr…

cs.CL2021

Learning from Language Description: Low-shot Named Entity Recognition via Decomposed Framework

Yaqing Wang, Haoda Chu, Chao Zhang +1

In this work, we study the problem of named entity recognition (NER) in a low resource scenario, focusing on few-shot and zero-shot settings. Built upon large-scale pre-trained lan…

cs.CL2020★ 34 cited

Adaptive Self-training for Few-shot Neural Sequence Labeling

Yaqing Wang, Subhabrata Mukherjee, Haoda Chu +4

Sequence labeling is an important technique employed for many Natural Language Processing (NLP) tasks, such as Named Entity Recognition (NER), slot tagging for dialog systems and s…

cs.CL2020★ 1 cited

Efficient Knowledge Graph Validation via Cross-Graph Representation Learning

Yaqing Wang, Fenglong Ma, Jing Gao

Recent advances in information extraction have motivated the automatic construction of huge Knowledge Graphs (KGs) by mining from large-scale text corpus. However, noisy facts are…

cs.CL2020★ 3 cited

Automatic Validation of Textual Attribute Values in E-commerce Catalog by Learning with Limited Labeled Data

Yaqing Wang, Yifan Ethan Xu, Xian Li +2

Product catalogs are valuable resources for eCommerce website. In the catalog, a product is associated with multiple attributes whose values are short texts, such as product name,…