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Unsupervised domain adaptation (UDA) with pre-trained language models (PrLM) has achieved promising results since these pre-trained models embed generic knowledge learned from various domains.
Adapterfusion: Non-destructive task composition for transfer learning
J. Pfeiffer, A. Kamath, A. Rücklé, K. Cho, and I. Gurevych · 2005
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Domain adaptation with structural correspondence learning
J. Blitzer, R. McDonald, and F. Pereira · 2006
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Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification
J. Blitzer, M. Dredze, and F. Pereira · 2007
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Visualizing data using t-sne
L. Van der Maaten and G. Hinton · 2008
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Cross-domain sentiment classification via spectral feature alignment
S. J. Pan, X. Ni, J.-T. Sun, Q. Yang, and Z. Chen · 2010
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Domain adaptation for large-scale sentiment classification: A deep learning approach
X. Glorot, A. Bordes, and Y. Bengio · 2011
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Marginalized denoising autoencoders for domain adaptation
M. Chen, Z. Xu, K. Weinberger, and F. Sha · 2012
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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
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Unsupervised domain adaptation by backpropagation
Y. Ganin and V. S. Lempitsky · 2015
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Domain separation networks
K. Bousmalis, G. Trigeorgis, N. Silberman, D. Krishnan, and D. Erhan · 2016
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Domain-adversarial training of neural networks
Y. Ganin, E. Ustinova, H. Ajakan, P. Germain, H. Larochelle, F. Laviolette, M. Marchand, and V. Lempitsky · 2016
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Gaussian error linear units (gelus)
D. Hendrycks and K. Gimpel · 2016
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Learning multiple visual domains with residual adapters
S.-A. Rebuffi, H. Bilen, and A. Vedaldi · 2017
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Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin · 2017
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Xnli: Evaluating cross-lingual sentence representations
A. Conneau, R. Rinott, G. Lample, A. Williams, S. Bowman, H. Schwenk, and V. Stoyanov · 2018
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Universal language model fine-tuning for text classification
J. Howard and S. Ruder · 2018
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Strong baselines for neural semi-supervised learning under domain shift
S. Ruder and B. Plank · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova · 2019
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Unsupervised domain adaptation of contextualized embeddings for sequence labeling
X. Han and J. Eisenstein · 2019
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Parameter-efficient transfer learning for nlp
N. Houlsby, A. Giurgiu, S. Jastrzebski, B. Morrone, Q. De Laroussilhe, A. Gesmundo, M. Attariyan, and S. Gelly · 2019
Semi-supervised learning on meta structure: Multi-task tagging and parsing in low-resource scenarios
K. Lim, J. Y. Lee, J. Carbonell, and T. Poibeau · 2020
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Adapterhub: A framework for adapting transformers
J. Pfeiffer, A. Rücklé, C. Poth, A. Kamath, I. Vulić, S. Ruder, K. Cho, and I. Gurevych · 2020
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Mad-x: An adapter-based framework for multi-task cross-lingual transfer
J. Pfeiffer, I. Vulić, I. Gurevych, and S. Ruder · 2020
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Neural unsupervised domain adaptation in nlp—a survey
A. Ramponi and B. Plank · 2020
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Orthogonal language and task adapters in zero-shot cross-lingual transfer
M. Vidoni, I. Vulić, and G. Glavaš · 2020
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Semi-supervised domain adaptation for dependency parsing
Z. Li, X. Peng, M. Zhang, R. Wang, and L. Si · 2019
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Roberta: A robustly optimized bert pretraining approach
Y. Liu, M. Ott, N. Goyal, J. Du, M. Joshi, D. Chen, O. Levy, M. Lewis, L. Zettlemoyer, and V. Stoyanov · 2019
Cited alongside, same era.
Domain adaptation with bert-based domain classification and data selection
X. Ma, P. Xu, Z. Wang, R. Nallapati, and B. Xiang · 2019
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Task refinement learning for improved accuracy and stability of unsupervised domain adaptation
Y. Ziser and R. Reichart · 2019
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Perl: Pivot-based domain adaptation for pre-trained deep contextualized embedding models
E. Ben-David, C. Rabinovitz, and R. Reichart · 2020
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Unsupervised cross-lingual representation learning at scale
A. Conneau, K. Khandelwal, N. Goyal, V. Chaudhary, G. Wenzek, F. Guzmán, E. Grave, M. Ott, L. Zettlemoyer, and V. Stoyanov · 2020
Cited alongside, same era.
R. Wang, D. Tang, N. Duan, Z. Wei, X. Huang, C. Cao, D. Jiang, M. Zhou, et al · 2020
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Robust transfer learning with pretrained language models through adapters
W. Han, B. Pang, and Y. Wu · 2021
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On the effectiveness of adapter-based tuning for pretrained language model adaptation
R. He, L. Liu, H. Ye, Q. Tan, B. Ding, L. Cheng, J.-W. Low, L. Bing, and L. Si · 2021
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Udalm: Unsupervised domain adaptation through language modeling
C. Karouzos, G. Paraskevopoulos, and A. Potamianos · 2021
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The adapter-bot: All-in-one controllable conversational model
Z. Lin, A. Madotto, Y. Bang, and P. Fung · 2021
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Parameter-efficient multi-task fine-tuning for transformers via shared hypernetworks
R. K. Mahabadi, S. Ruder, M. Dehghani, and J. Henderson · 2021
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What to pre-train on? efficient intermediate task selection
C. Poth, J. Pfeiffer, A. Rücklé, and I. Gurevych · 2021
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Adaptsum: Towards low-resource domain adaptation for abstractive summarization
T. Yu, Z. Liu, and P. Fung · 2021
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