TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK
Question Quality Assessment	CrowdSource QA	BERT	MSE	0.046	# 1
Common Sense Reasoning	CrowdSource QA	BERT	MSE	0.046	# 1
Community Question Answering	CrowdSource QA	BERT	MSE	0.046	# 1
Reading Comprehension	CrowdSource QA	BERT	MSE	0.046	# 1

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Predicting Subjective Features of Questions of QA Websites using BERT

ICWR 2020 • Issa Annamoradnejad • Mohammadamin Fazli • Jafar Habibi

Community Question-Answering websites, such as StackOverflow and Quora, expect users to follow specific guidelines in order to maintain content quality. These systems mainly rely on community reports for assessing contents, which has serious problems such as the slow handling of violations, the loss of normal and experienced users' time, the low quality of some reports, and discouraging feedback to new users... (read more)

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TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK	BENCHMARK
Question Quality Assessment	CrowdSource QA	BERT	MSE	0.046	# 1	Compare
Common Sense Reasoning	CrowdSource QA	BERT	MSE	0.046	# 1	Compare
Community Question Answering	CrowdSource QA	BERT	MSE	0.046	# 1	Compare
Reading Comprehension	CrowdSource QA	BERT	MSE	0.046	# 1	Compare

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METHOD	TYPE
Residual Connection	Skip Connections
Attention Dropout	Regularization
Linear Warmup With Linear Decay	Learning Rate Schedules
Weight Decay	Regularization
GELU	Activation Functions
Dense Connections	Feedforward Networks
Adam	Stochastic Optimization
WordPiece	Subword Segmentation
Softmax	Output Functions
Dropout	Regularization
Multi-Head Attention	Attention Modules
Layer Normalization	Normalization
Scaled Dot-Product Attention	Attention Mechanisms
BERT	Language Models

Predicting Subjective Features of Questions of QA Websites using BERT

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