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Models/SWEM-concat

SWEM-concat

Reported on 16 benchmarks across 7 tasks · 1 paper · 6 SOTA

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

Natural Language Processing13 results

Semantic Textual SimilarityonMSRP
Accuracy· 2018-05-24
71.5
best: 80.41 (FEAT2, TFKLD, SVM, Fine-grained features)
SOTA
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
Semantic Textual SimilarityonMSRP
F1· 2018-05-24
81.3
best: 85.96 (FEAT2, TFKLD, SVM, Fine-grained features)
SOTA
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
Paraphrase IdentificationonMSRP
Accuracy· 2018-05-24
71.5
best: 80.41 (FEAT2, TFKLD, SVM, Fine-grained features)
SOTA
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
Paraphrase IdentificationonMSRP
F1· 2018-05-24
81.3
best: 85.96 (FEAT2, TFKLD, SVM, Fine-grained features)
SOTA
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
Text ClassificationonYahoo! Answers
Accuracy· 2018-05-24
73.53
best: 77.62 (BERT-ITPT-FiT)
SOTA
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
Question AnsweringonWikiQA
MAP· 2018-05-24
0.6788
best: 0.927 (TANDA-DeBERTa-V3-Large + ALL)
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
Question AnsweringonWikiQA
MRR· 2018-05-24
0.6908
best: 0.939 (TANDA-DeBERTa-V3-Large + ALL)
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
Sentiment AnalysisonMR
Accuracy· 2018-05-24
78.2
best: 93.3 (VLAWE)
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
Sentiment AnalysisonSST-5 Fine-grained classification
Accuracy· 2018-05-24
46.1
best: 62.27 (Llama-3.3-70B + CAPO)
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
Sentiment AnalysisonSST-2 Binary classification
Accuracy· 2018-05-24
84.3
best: 97.5 (T5-11B)
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
Subjectivity AnalysisonSUBJ
Accuracy· 2018-05-24
93
best: 97.34 (RoBERTa+DualCL)
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
Text ClassificationonDBpedia
Error· 2018-05-24
1.43
best: 0.62 (XLNet)
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
Text ClassificationonAG News
Error· 2018-05-24
7.34
best: 4.45 (XLNet)
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843

Methodology3 results

ClassificationonYahoo! Answers
Accuracy· 2018-05-24
73.53
best: 77.62 (BERT-ITPT-FiT)
SOTA
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
ClassificationonDBpedia
Error· 2018-05-24
1.43
best: 0.62 (XLNet)
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843
ClassificationonAG News
Error· 2018-05-24
7.34
best: 4.45 (XLNet)
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms arXiv:1805.09843