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Models/NABoE-full

NABoE-full

Reported on 8 benchmarks across 2 tasks · 1 paper · 4 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing4 results

Text ClassificationonR8
F-measure· 2019-09-03
91.7
SOTA
Neural Attentive Bag-of-Entities Model for Text Classification arXiv:1909.01259
Text Classificationon20NEWS
F-measure· 2019-09-03
86.2
best: 93 (LinearSVM+TFIDF)
SOTA
Neural Attentive Bag-of-Entities Model for Text Classification arXiv:1909.01259
Text ClassificationonR8
Accuracy· 2019-09-03
97.1
best: 98.451 (DeBERTa)
Neural Attentive Bag-of-Entities Model for Text Classification arXiv:1909.01259
Text Classificationon20NEWS
Accuracy· 2019-09-03
86.8
best: 93 (LinearSVM+TFIDF)
Neural Attentive Bag-of-Entities Model for Text Classification arXiv:1909.01259

Methodology4 results

ClassificationonR8
F-measure· 2019-09-03
91.7
SOTA
Neural Attentive Bag-of-Entities Model for Text Classification arXiv:1909.01259
Classificationon20NEWS
F-measure· 2019-09-03
86.2
best: 93 (LinearSVM+TFIDF)
SOTA
Neural Attentive Bag-of-Entities Model for Text Classification arXiv:1909.01259
ClassificationonR8
Accuracy· 2019-09-03
97.1
best: 98.451 (DeBERTa)
Neural Attentive Bag-of-Entities Model for Text Classification arXiv:1909.01259
Classificationon20NEWS
Accuracy· 2019-09-03
86.8
best: 93 (LinearSVM+TFIDF)
Neural Attentive Bag-of-Entities Model for Text Classification arXiv:1909.01259