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SOTA
自然语言理解
Natural Language Understanding On Pdp60
Natural Language Understanding On Pdp60
评估指标
Accuracy
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Accuracy
Paper Title
Repository
HNN
90
A Hybrid Neural Network Model for Commonsense Reasoning
UDSSM-II (ensemble)
78.3
Unsupervised Deep Structured Semantic Models for Commonsense Reasoning
-
BERT-large 340M
78.3
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
UDSSM-I (ensemble)
76.7
Unsupervised Deep Structured Semantic Models for Commonsense Reasoning
-
UDSSM-II
75
Unsupervised Deep Structured Semantic Models for Commonsense Reasoning
-
DSSM
75.0
Unsupervised Deep Structured Semantic Models for Commonsense Reasoning
-
BERT-base 110M + MAS
68.3
Attention Is (not) All You Need for Commonsense Reasoning
USSM + Supervised Deepnet + 3 Knowledge Bases
66.7
Attention Is (not) All You Need for Commonsense Reasoning
Word-level CNN+LSTM (full scoring)
60.0
A Simple Method for Commonsense Reasoning
Subword-level Transformer LM
58.3
Attention Is All You Need
USSM + Cause-Effect Knowledge Base
55.0
Probabilistic Reasoning via Deep Learning: Neural Association Models
-
Word-level CNN+LSTM (partial scoring)
53.3
A Simple Method for Commonsense Reasoning
USSM + Supervised Deepnet
53.3
Attention Is (not) All You Need for Commonsense Reasoning
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