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20172023
most citedAutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types

69 citations · 146 across the 12 of their papers we have counts for

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14 papers · 1 filter

cs.CL2022

Gradient Imitation Reinforcement Learning for General Low-Resource Information Extraction

Xuming Hu, Shiao Meng, Chenwei Zhang +4

Information Extraction (IE) aims to extract structured information from heterogeneous sources. IE from natural language texts include sub-tasks such as Named Entity Recognition (NE…

cs.CL2020

Dynamic Semantic Matching and Aggregation Network for Few-shot Intent Detection

Hoang Nguyen, Chenwei Zhang, Congying Xia +1

Few-shot Intent Detection is challenging due to the scarcity of available annotated utterances. Although recent works demonstrate that multi-level matching plays an important role…

cs.CL2020

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.CL202018 cited

Octet: Online Catalog Taxonomy Enrichment with Self-Supervision

Yuning Mao, Tong Zhao, Andrey Kan +4

Taxonomies have found wide applications in various domains, especially online for item categorization, browsing, and search. Despite the prevalent use of online catalog taxonomies,…

cs.CL202035 cited

CG-BERT: Conditional Text Generation with BERT for Generalized Few-shot Intent Detection

Congying Xia, Chenwei Zhang, Hoang Nguyen +2

In this paper, we formulate a more realistic and difficult problem setup for the intent detection task in natural language understanding, namely Generalized Few-Shot Intent Detecti…

cs.CL2020

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…