Afterv1.0
Python source code for EMNLP 2020 Findings paper: "Domain Adversarial Fine-Tuning as an Effective Regularizer".
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Domain Adapted Atsc | 128 | 3 years ago | 5 | mit | Python | |||||
| code for our 2019 paper: "Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment Classification" | ||||||||||
| Cross Domain_ner | 45 | 4 years ago | 5 | Python | ||||||
| Cross-domain NER using cross-domain language modeling, code for ACL 2019 paper | ||||||||||
| Pblm Domain Adaptation | 8 | 5 years ago | Python | |||||||
| The code base for the article "Pivot Based Language Modeling for Improved Neural Domain Adaptation", NAACL 2018 | ||||||||||
| Afterv1.0 | 6 | 3 years ago | Python | |||||||
| Python source code for EMNLP 2020 Findings paper: "Domain Adversarial Fine-Tuning as an Effective Regularizer". | ||||||||||
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Python
Language Model
Tuning
Domain Adaptation
Lms
Adversarial Learning