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600-dimensional sentence vector representations created by the model described in the paper "Refining Raw Sentence Representations for Textual Entailment Recognition via Attention". The dataset is in tab-delimited format: ID\tSENTENCE_TYPE\tVECTOR, where ID is the id corresponding to the sentence pair as specified in the Repeval 2017 test dataset for both matched and mismatched evaluations, available in https://inclass.kaggle.com/c/multinli-matched-evaluation/download/multinli_0.9_test_matched_unlabeled.jsonl and https://inclass.kaggle.com/c/multinli-mismatched-evaluation/download/multinli_0.9_test_mismatched_unlabeled.jsonl (you will probably have to create an account to download them). SENTENCE_TYPE can either be p, meaning the sentence is the premise or h, meaning it is the hypothesis. VECTOR is a space-delimited 600-dim vector.
sentence representation, sentence embedding
sentence representation, sentence embedding
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 9 |

Views provided by UsageCounts