Distributional Correspondence Indexing

Reported on 5 benchmarks across 1 task · 1 paper · 5 SOTA

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

Natural Language Processing5 results

Sentiment AnalysisonMulti-Domain Sentiment Dataset
Average· 2018-10-19
83.3
best: 91.74 (UDALM: Unsupervised Domain Adaptation through Language Modeling)
SOTA
Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New Experiments arXiv:1810.09311
Sentiment AnalysisonMulti-Domain Sentiment Dataset
Books· 2018-10-19
81.4
best: 90.63 (UDALM: Unsupervised Domain Adaptation through Language Modeling)
SOTA
Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New Experiments arXiv:1810.09311
Sentiment AnalysisonMulti-Domain Sentiment Dataset
DVD· 2018-10-19
81
best: 89.78 (UDALM: Unsupervised Domain Adaptation through Language Modeling)
SOTA
Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New Experiments arXiv:1810.09311
Sentiment AnalysisonMulti-Domain Sentiment Dataset
Electronics· 2018-10-19
8506
SOTA
Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New Experiments arXiv:1810.09311
Sentiment AnalysisonMulti-Domain Sentiment Dataset
Kitchen· 2018-10-19
85.9
best: 93.77 (UDALM: Unsupervised Domain Adaptation through Language Modeling)
SOTA
Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New Experiments arXiv:1810.09311