| named-entity-recognition-ner-on-conll-2003 | SWEM-CRF | #66 | F1: 86.28 |
| natural-language-inference-on-multinli | SWEM-max | #43 | Matched: 68.2Mismatched: 67.7 |
| natural-language-inference-on-snli | SWEM-max | #58 | % Test Accuracy: 83.8 |
| question-answering-on-quora-question-pairs | SWEM-concat | #16 | Accuracy: 83.03% |
| question-answering-on-wikiqa | SWEM-concat | #12 | MAP: 0.6788MRR: 0.6908 |
| sentiment-analysis-on-mr | SWEM-concat | #10 | Accuracy: 78.2 |
| sentiment-analysis-on-sst-2-binary | SWEM-concat | #71 | Accuracy: 84.3 |
| sentiment-analysis-on-sst-5-fine-grained | SWEM-concat | #20 | Accuracy: 46.1 |
| sentiment-analysis-on-yelp-binary | SWEM-hier | #12 | Error: 4.19 |
| sentiment-analysis-on-yelp-fine-grained | SWEM-hier | #13 | Error: 36.21 |
| subjectivity-analysis-on-subj | SWEM-concat | #12 | Accuracy: 93 |
| text-classification-on-ag-news | SWEM-concat | #9 | Error: 7.34 |
| text-classification-on-dbpedia | SWEM-concat | #16 | Error: 1.43 |
| text-classification-on-trec-6 | SWEM-aver | #15 | Error: 7.8 |
| text-classification-on-yahoo-answers | SWEM-concat | #7 | Accuracy: 73.53 |