LEAM

Reported on 6 benchmarks across 3 tasks · 1 paper

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

Natural Language Processing4 results

Sentiment AnalysisonYelp Fine-grained classification
Error· 2018-05-10
35.91
best: 27.05 (XLNet)
Joint Embedding of Words and Labels for Text Classification arXiv:1805.04174
Sentiment AnalysisonYelp Binary classification
Error· 2018-05-10
4.69
best: 1.37 (XLNet)
Joint Embedding of Words and Labels for Text Classification arXiv:1805.04174
Text ClassificationonDBpedia
Error· 2018-05-10
0.98
best: 0.62 (XLNet)
Joint Embedding of Words and Labels for Text Classification arXiv:1805.04174
Text ClassificationonAG News
Error· 2018-05-10
7.55
best: 4.45 (XLNet)
Joint Embedding of Words and Labels for Text Classification arXiv:1805.04174

Methodology2 results

ClassificationonDBpedia
Error· 2018-05-10
0.98
best: 0.62 (XLNet)
Joint Embedding of Words and Labels for Text Classification arXiv:1805.04174
ClassificationonAG News
Error· 2018-05-10
7.55
best: 4.45 (XLNet)
Joint Embedding of Words and Labels for Text Classification arXiv:1805.04174