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nlp:domain_adaptation [2023/03/02 04:55] – [Papers (General Domain Adaptation in NLP)] jmflanignlp:domain_adaptation [2023/06/15 07:36] (current) – external edit 127.0.0.1
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   * [[https://arxiv.org/pdf/1812.02849.pdf|2018 - A Survey of Unsupervised Deep Domain Adaptation]] Unsupervised domain adaptation differs from regular domain adaptation in that you don't get to see labeled examples in the domain of interest, only unlabeled examples.   * [[https://arxiv.org/pdf/1812.02849.pdf|2018 - A Survey of Unsupervised Deep Domain Adaptation]] Unsupervised domain adaptation differs from regular domain adaptation in that you don't get to see labeled examples in the domain of interest, only unlabeled examples.
   * [[https://arxiv.org/pdf/1806.00258.pdf|Chu & Wang 2018 - A Survey of Domain Adaptation for Neural Machine Translation]]   * [[https://arxiv.org/pdf/1806.00258.pdf|Chu & Wang 2018 - A Survey of Domain Adaptation for Neural Machine Translation]]
-  * [[https://arxiv.org/pdf/2006.00632.pdf|Ramponi & Plank 2020 - Neural Unsupervised Domain Adaptation in NLP -A Survey]]+  * [[https://arxiv.org/pdf/2006.00632.pdf|Ramponi & Plank 2020 - Neural Unsupervised Domain Adaptation in NLP - A Survey]]
  
 ===== Domain Adaptation (Outside of NLP) ===== ===== Domain Adaptation (Outside of NLP) =====
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 ===== Papers (General Domain Adaptation in NLP) ===== ===== Papers (General Domain Adaptation in NLP) =====
-See also [[https://www.aminer.org/topic/5faa648192c7f9be21f70f88|Awesome Neural Adaptation in NLP]] A curated list of unsupervised domain adaption papers in NLP (not including MT).+See also [[https://github.com/bplank/awesome-neural-adaptation-in-NLP|Awesome Neural Adaptation in NLP]] or [[https://www.aminer.org/topic/5faa648192c7f9be21f70f88|here (old)]] A curated list of unsupervised domain adaption papers in NLP (not including MT).
   * [[https://arxiv.org/pdf/0907.1815.pdf|Daumé III 2009 - Frustratingly Easy Domain Adaptation]]  A seminal paper, the baseline that you should always try (for linear models).   * [[https://arxiv.org/pdf/0907.1815.pdf|Daumé III 2009 - Frustratingly Easy Domain Adaptation]]  A seminal paper, the baseline that you should always try (for linear models).
   * The obvious baseline for neural networks is to fine-tune a pre-trained network on the new domain.  I don't know any papers looking into this method and the trade-off associated with it, but there should be one   * The obvious baseline for neural networks is to fine-tune a pre-trained network on the new domain.  I don't know any papers looking into this method and the trade-off associated with it, but there should be one
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   * [[https://aclanthology.org/2021.emnlp-main.566.pdf|Kulshreshtha et al 2021 - Back-Training excels Self-Training at Unsupervised Domain Adaptation of Question Generation and Passage Retrieval]] Back-training: generating noisy inputs given outputs (vs self-training: generating noisy outputs given inputs).   * [[https://aclanthology.org/2021.emnlp-main.566.pdf|Kulshreshtha et al 2021 - Back-Training excels Self-Training at Unsupervised Domain Adaptation of Question Generation and Passage Retrieval]] Back-training: generating noisy inputs given outputs (vs self-training: generating noisy outputs given inputs).
   * [[https://aclanthology.org/2022.naacl-main.96.pdf|Chronopoulou et al 2022 - Efficient Hierarchical Domain Adaptation for Pretrained Language Models]]   * [[https://aclanthology.org/2022.naacl-main.96.pdf|Chronopoulou et al 2022 - Efficient Hierarchical Domain Adaptation for Pretrained Language Models]]
 +  * [[https://arxiv.org/pdf/2302.03169.pdf|Xie et al 2023 - Data Selection for Language Models via Importance Resampling]]
 +  * [[https://arxiv.org/pdf/2302.03194.pdf|Malik et al 2023 - UDApter - Efficient Domain Adaptation Using Adapters]]
  
 {{media:domain_adaptation_table2020.png}}\\ {{media:domain_adaptation_table2020.png}}\\
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 ===== Related Pages ===== ===== Related Pages =====
   * [[Data Augmentation]]   * [[Data Augmentation]]
 +  * [[ml:Fine-Tuning]]
   * [[ml:Semi-supervised Learning]]   * [[ml:Semi-supervised Learning]]
  
nlp/domain_adaptation.1677732924.txt.gz · Last modified: 2023/06/15 07:36 (external edit)
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