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20182021
most citedSemi-Supervised Models via Data Augmentationfor Classifying Interactive Affective Responses

11 citations · 15 across the 2 of their papers we have counts for

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6 papers · 1 filter

cs.CL2021

GroupLink: An End-to-end Multitask Method for Word Grouping and Relation Extraction in Form Understanding

Zilong Wang, Mingjie Zhan, Houxing Ren +4

Forms are a common type of document in real life and carry rich information through textual contents and the organizational structure. To realize automatic processing of forms, wor…

cs.CL20214 cited

SG-Net: Syntax Guided Transformer for Language Representation

Zhuosheng Zhang, Yuwei Wu, Junru Zhou +3

Understanding human language is one of the key themes of artificial intelligence. For language representation, the capacity of effectively modeling the linguistic knowledge from th…

cs.CL202011 cited

Semi-Supervised Models via Data Augmentationfor Classifying Interactive Affective Responses

Jiaao Chen, Yuwei Wu, Diyi Yang

We present semi-supervised models with data augmentation (SMDA), a semi-supervised text classification system to classify interactive affective responses. SMDA utilizes recent tran…

cs.CL2019

Semantics-aware BERT for Language Understanding

Zhuosheng Zhang, Yuwei Wu, Hai Zhao +4

The latest work on language representations carefully integrates contextualized features into language model training, which enables a series of success especially in various machi…

cs.CL2019

SG-Net: Syntax-Guided Machine Reading Comprehension

Zhuosheng Zhang, Yuwei Wu, Junru Zhou +3

For machine reading comprehension, the capacity of effectively modeling the linguistic knowledge from the detail-riddled and lengthy passages and getting ride of the noises is esse…

cs.CL2018

Explicit Contextual Semantics for Text Comprehension

Zhuosheng Zhang, Yuwei Wu, Zuchao Li +1

Who did what to whom is a major focus in natural language understanding, which is right the aim of semantic role labeling (SRL) task. Despite of sharing a lot of processing charact…