paper-with-me

Sentiment Analysis 벤치마크

Sentiment Analysis on Multi-Domain Sentiment Dataset

6개 결과 · ⬇ CSV · JSON

DVD

75.4 79 82.59 86.19 89.78 2015-05 2026-09 DANN — 75.4 (2015-05-28) VFAE — 76.57 (2015-11-03) Asymmetric tri-training — 76.17 (2017-02-27) Multi-task tri-training — 78.14 (2018-04-25) Distributional Correspondence Indexing — 81.0 (2018-10-19) UDALM: Unsupervised Domain Adaptation through Language Modeling — 89.78 (2021-04-14) DANN — 75.4 (2015-05-28) VFAE — 76.57 (2015-11-03) Multi-task tri-training — 78.14 (2018-04-25) Distributional Correspondence Indexing — 81.0 (2018-10-19) UDALM: Unsupervised Domain Adaptation through Language Modeling — 89.78 (2021-04-14)
RankModel DVDBooksElectronicsKitchenAverage PaperCodeYear
1 UDALM: Unsupervised Domain Adaptation through Language Modeling 89.7890.6392.7893.7791.74 UDALM: Unsupervised Domain Adaptation through Language Modeling ckarouzos/slp_daptmlm 2021
2 Distributional Correspondence Indexing 81.0081.485,0685.983.30 Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New Experiments AlexMoreo/pydci 2018
3 Multi-task tri-training 78.1474.8681.4582.1479.15 Strong Baselines for Neural Semi-supervised Learning under Domain Shift bplank/semi-supervised-baselines · ambujojha/SemiSupervisedLearning 2018
4 VFAE 76.5773.4080.5382.9378.36 The Variational Fair Autoencoder nctumllab/huang-ching-wei · yevgeni-integrate-ai/vfae 2015
5 Asymmetric tri-training 76.1772.9780.4783.9778.39 Asymmetric Tri-training for Unsupervised Domain Adaptation ksaito-ut/atda 2017
6 DANN 75.471.4377.6780.5376.26 Domain-Adversarial Training of Neural Networks PaddlePaddle/PaddleSpeech · thuml/Transfer-Learning-Library · facebookresearch/DomainBed · +34 2015
1–6 / 6 페이지당 10 20 50 100