| Benchmark | Model | Rank | Results |
|---|---|---|---|
| question-answering-on-wikiqa | MMA-NSE attention | #11 | MAP: 0.6811MRR: 0.6993 |
| natural-language-inference-on-snli | 300D MMA-NSE encoders with attention | #50 | % Test Accuracy: 85.4% Train Accuracy: 86.9Parameters: 3.2m |
| natural-language-inference-on-snli | 300D NSE encoders | #53 | % Test Accuracy: 84.6% Train Accuracy: 86.2Parameters: 3.0m |
| sentiment-analysis-on-sst-2-binary-classification | Neural Semantic Encoder | #61 | Accuracy: 89.7 |
| machine-translation-on-wmt2014-english-german | NSE-NSE | #77 | BLEU score: 17.9 |